SpatialGym Dashboard

🔄 Turn 1

👤 Environment Observation (click to toggle)
# Spatial Exploration Task

You are a spatial reasoner in a 2D, text-only N×M grid. Every object including you is a point at integer (x, y) coordinates.

Goal: **Minimize total COST** while building a complete and accurate map of the environment.

Multi-room rules (may exist multiple rooms):
- Your ...

🤔 Assistant Thinking (click to toggle)
Start by observing from the initial position (0,0) facing north to identify visible objects/doors in Room 1 and plan efficient jumps to doors or dense object clusters....

💬 Assistant Action
Actions: [Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Place agent at origin facing north; assign the yellow door an integer coordinate consistent with front-slight-right and mid distance (e.g., [1,3]).
FINAL ANSWER:
{
"agent": { "position": [0, 0], "facing": "north" },
"yellow door": { "position": [1, 3] }
}...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "north"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  }
}

🎯 Ground Truth (Observed)

{
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "north"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "north"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Encode the only observed entity (yellow door) in the agent-relative local frame; place it slightly to the right and forward at a mid-distance integer coordinate, with door facing toward the agent.
FINAL ANSWER:
{
"origin": "agent",
"objects": {
"yellow door": {
"position": [1, 3...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "yellow door": {
      "position": [
        1,
        3
      ],
      "facing": "-y"
    }
  }
}

🎯 Ground Truth

{
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  }
}

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "yellow door": {
      "position": [
        1,
        3
      ],
      "facing": "-y"
    }
  }
}

🎯 Ground Truth

{
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  }
}

🌫️ Fog Probe Response (click to toggle)
THINK: Only the yellow door has been observed so far; all candidate points A-F lie in regions not yet observed (outside current FOV and/or behind walls), so they are unexplored.
FINAL ANSWER:
{
"unexplored": ["A", "B", "C", "D", "E", "F"]
}...

🗺️ Symbolic Fog Map

###############
###......######
###......######
###......######
###......######
###......######
###......######
######+########
#....C.########
#...A.F#......#
#....*.#......#
#.E....#......#
#..D...+......#
#..B...#......#
########......#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F

🤖 Predicted: A, B, C, D, E, F

🎯 Ground Truth: E, B, D

🧠 Cognitive Map Metrics

Global:

dir: 1

facing: 1

pos: 1

overall: 1

Global (Full):

dir: 0.025

facing: 0.111

pos: 0.133

overall: 0.090

Local:

dir: 1

facing: 1

pos: 1

overall: 1

Local (Newly):

dir: 1

facing: 1

pos: 1

overall: 1

Fog Probe:

precision: 0.500

recall: 1

overall: 0.667

📈 Turn Metrics

node_coverage: 0.071

edge_coverage: 0.024

is_action_fail: False

step: 1

action_counts:

move: 0

rotate: 0

return: 0

observe: 1

term: 0

forced_term: 0

query: 0

information_gain: 0.071

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 2

👤 Environment Observation (click to toggle)
You observe:
• yellow door: front-slight-right, mid distance, on front wall.
You have a maximum of 19 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
Jump to the yellow door (only known landmark) to reach the doorway and gain visibility into both connected rooms from the threshold....

💬 Assistant Action
Actions: [JumpTo(yellow door), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Assign integer coordinates consistent with observed bearings/distances and proximity constraints, using origin at initial agent position and keeping agent now at the yellow door.
FINAL ANSWER:
{
"agent": { "position": [1, 3], "facing": "north" },
"yellow door": { "position": [1, 3] },
"...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "television": {
    "position": [
      0,
      6
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      6
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      8
    ]
  },
  "plant": {
    "position": [
      0,
      8
    ]
  }
}

🎯 Ground Truth (Observed)

{
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Use integer approximate positions consistent with observed egocentric bearings/distances; include facings only where specified; origin is agent at the yellow door.
FINAL ANSWER:
{
"origin": "agent",
"objects": {
"yellow door": { "position": [0, 0] },
"television": { "position": [-...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "yellow door": {
      "position": [
        0,
        0
      ]
    },
    "television": {
      "position": [
        -2,
        3
      ],
      "facing": "+y"
    },
    "cap": {
      "position": [
        2,
        3
      ],
      "facing": "+x"
    },
    "basket": {
      "position": [
        1,
        6
      ]
    },
    "plant": {
      "position": [
        -1,
        6
      ]
    }
  }
}

🎯 Ground Truth

{
  "plant": {
    "position": [
      -1,
      6
    ],
    "facing": "east"
  },
  "cap": {
    "position": [
      1,
      2
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      -1,
      2
    ],
    "facing": "north"
  },
  "basket": {
    "position": [
      1,
      4
    ],
    "facing": "east"
  }
}

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "yellow door": {
      "position": [
        0,
        0
      ]
    },
    "television": {
      "position": [
        -2,
        3
      ],
      "facing": "+y"
    },
    "cap": {
      "position": [
        2,
        3
      ],
      "facing": "+x"
    },
    "basket": {
      "position": [
        1,
        6
      ]
    },
    "plant": {
      "position": [
        -1,
        6
      ]
    }
  }
}

🎯 Ground Truth

{
  "plant": {
    "position": [
      -1,
      6
    ],
    "facing": "east"
  },
  "cap": {
    "position": [
      1,
      2
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      -1,
      2
    ],
    "facing": "north"
  },
  "basket": {
    "position": [
      1,
      4
    ],
    "facing": "east"
  }
}

🌫️ Fog Probe Response (click to toggle)
THINK: We have only observed through the yellow door into the upper room area; the candidate points in the lower-left room remain unobserved/unexplored.
FINAL ANSWER: {
"unexplored": ["B", "E", "F", "J", "K", "L"]
}...

🗺️ Symbolic Fog Map

###############
###.H....######
###......######
###......######
###.....D######
###I....A######
###C....G######
######*########
#....F.########
#....B.#......#
#...JE.#......#
#....K.#......#
#......+......#
#..L...#......#
########......#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F, G, H, I, J, K, L

🤖 Predicted: B, E, F, J, K, L

🎯 Ground Truth: L, K, J, G, C, I

🧠 Cognitive Map Metrics

Global:

dir: 0.762

facing: 1

pos: 0.871

overall: 0.878

Global (Full):

dir: 0.133

facing: 0.333

pos: 0.348

overall: 0.272

Local:

dir: 0.900

facing: 1

pos: 0.788

overall: 0.896

Local (Newly):

dir: 0.900

facing: 1

pos: 0.788

overall: 0.896

Fog Probe:

precision: 0.500

recall: 0.500

overall: 0.500

📈 Turn Metrics

node_coverage: 0.357

edge_coverage: 0.122

is_action_fail: False

step: 2

action_counts:

move: 1

rotate: 0

return: 0

observe: 2

term: 0

forced_term: 0

query: 0

information_gain: 0.332

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 3

👤 Environment Observation (click to toggle)
You jumped to yellow door. You observe:
• television: front-left, mid distance, facing forward
• cap: front-right, mid distance, facing right
• basket: front-slight-right, slightly far
• plant: front-slight-left, slightly far
Assume your current facing direction is called "north":
• television is w...

🤔 Assistant Thinking (click to toggle)
From the doorway, rotating should reveal additional objects and possibly the brown door while keeping the advantage of seeing into connected rooms. Rotate 90° clockwise to scan a new sector....

💬 Assistant Action
Actions: [Rotate(90), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Build a globally consistent integer-coordinate map using the initial pose as origin, placing the yellow door at a mid-distance front-slight-right location and positioning other observed objects relative to the agent at the doorway while satisfying the reported proximity constraints.
FINAL ANS...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ]
  },
  "plant": {
    "position": [
      0,
      7
    ]
  }
}

🎯 Ground Truth (Observed)

{
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "east"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "east"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: No objects are currently in my field of view after rotating; the local cognitive map should therefore contain an empty objects dictionary with origin at the agent.
FINAL ANSWER:
{
"origin": "agent",
"objects": {}
}...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {}
}

🎯 Ground Truth

(no data)

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {}
}

🎯 Ground Truth

(no data)

🌫️ Fog Probe Response (click to toggle)
THINK: Only observed from the yellow doorway facing north (and then east with no visibility). Candidate points south of the doorway and around the other door remain unobserved.
FINAL ANSWER: {"unexplored":["A","B","C","E","F","K"]}...

🗺️ Symbolic Fog Map

###############
###......######
###..I...######
###L.....######
###......######
###D..H..######
###GJ....######
######*########
#......########
#...C.F#......#
#....B.#......#
#A.....#......#
#......+......#
#....KE#......#
########......#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F, G, H, I, J, K, L

🤖 Predicted: A, B, C, E, F, K

🎯 Ground Truth: K, E, A, J, G, D

🧠 Cognitive Map Metrics

Global:

dir: 0.952

facing: 1

pos: 0.871

overall: 0.941

Global (Full):

dir: 0.167

facing: 0.333

pos: 0.348

overall: 0.283

Local:

(none)

Local (Newly):

(none)

Fog Probe:

precision: 0.500

recall: 0.500

overall: 0.500

📈 Turn Metrics

node_coverage: 0.357

edge_coverage: 0.122

is_action_fail: False

step: 3

action_counts:

move: 1

rotate: 1

return: 0

observe: 3

term: 0

forced_term: 0

query: 0

information_gain: 0.332

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 4

👤 Environment Observation (click to toggle)
You rotated clockwise 90°. You observe: No objects in field of view..
You have a maximum of 17 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
Current view (facing east) is empty; rotate 180° to face west and scan the opposite sector from the doorway, which may reveal the brown door or additional objects....

💬 Assistant Action
Actions: [Rotate(180), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Build an integer-coordinate global map consistent with all binned egocentric observations, jump-to-door relocation, rotations, and the stated proximity relations; convert observed object-facing (forward/right/left) into global cardinal facing based on the agent’s facing at the time of observa...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ]
  },
  "plant": {
    "position": [
      0,
      7
    ]
  },
  "shoes": {
    "position": [
      -3,
      0
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -4,
      0
    ]
  }
}

🎯 Ground Truth (Observed)

{
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "west"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "west"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Need a local, agent-centric map of only the currently visible objects (shoes, wine) with integer relative positions; include facing only for shoes (given).
FINAL ANSWER: {
"origin": "agent",
"objects": {
"shoes": {
"position": [-4, 5],
"facing": "-x"
},
"wine": {
...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "shoes": {
      "position": [
        -4,
        5
      ],
      "facing": "-x"
    },
    "wine": {
      "position": [
        -5,
        4
      ]
    }
  }
}

🎯 Ground Truth

{
  "shoes": {
    "position": [
      -4,
      5
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -2,
      4
    ],
    "facing": "east"
  }
}

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "shoes": {
      "position": [
        -4,
        5
      ],
      "facing": "-x"
    },
    "wine": {
      "position": [
        -5,
        4
      ]
    }
  }
}

🎯 Ground Truth

{
  "shoes": {
    "position": [
      -4,
      5
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -2,
      4
    ],
    "facing": "east"
  }
}

🌫️ Fog Probe Response (click to toggle)
THINK: We have only observed a few objects around the yellow doorway; none of the candidate locations A-F have been directly observed/covered yet, so they are all in currently unexplored regions.
FINAL ANSWER: {"unexplored":["A","B","C","D","E","F"]}...

🗺️ Symbolic Fog Map

###############
###......######
###......######
###......######
###......######
###......######
###......######
######*########
#......########
#.B..DC#......#
#......#......#
#..EA..#......#
#......+......#
#.....F#......#
########......#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F

🤖 Predicted: A, B, C, D, E, F

🎯 Ground Truth: E, A, F

🧠 Cognitive Map Metrics

Global:

dir: 0.889

facing: 1

pos: 0.845

overall: 0.911

Global (Full):

dir: 0.267

facing: 0.444

pos: 0.450

overall: 0.387

Local:

dir: 0.667

facing: 1

pos: 0.699

overall: 0.789

Local (Newly):

dir: 0.667

facing: 1

pos: 0.699

overall: 0.789

Fog Probe:

precision: 0.500

recall: 1

overall: 0.667

📈 Turn Metrics

node_coverage: 0.500

edge_coverage: 0.171

is_action_fail: False

step: 4

action_counts:

move: 1

rotate: 2

return: 0

observe: 4

term: 0

forced_term: 0

query: 0

information_gain: 0.413

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 5

👤 Environment Observation (click to toggle)
You rotated clockwise 180°. You observe:
• shoes: front-left, slightly far, facing left
• wine: front-left, slightly far.
You have a maximum of 16 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
We’ve scanned facing north (objects) and east (empty) and west (shoes/wine). Next, scan the remaining major sector by rotating to face south from the doorway; this may reveal additional Room 1 contents or another door....

💬 Assistant Action
Actions: [Rotate(-90), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Assign consistent integer coordinates using the agent’s initial origin (0,0) and observed relative bearings/distances; keep agent at the yellow door after JumpTo, with current facing south after the last rotation.
FINAL ANSWER:
{
"agent": { "position": [1, 3], "facing": "south" },
"yello...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "television": {
    "position": [
      0,
      6
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      6
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      3,
      7
    ]
  },
  "plant": {
    "position": [
      -1,
      7
    ]
  },
  "shoes": {
    "position": [
      -3,
      0
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -4,
      1
    ]
  },
  "scooter": {
    "position": [
      0,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -1,
      -2
    ],
    "facing": "south"
  },
  "brown door": {
    "position": [
      3,
      -1
    ]
  }
}

🎯 Ground Truth (Observed)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "south"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      1,
      3
    ],
    "facing": "south"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Build a local (agent-centric) map of only the currently visible items (scooter, backpack, brown door). Use the agent’s current facing as +y and encode object facings in local axes.
FINAL ANSWER:
```json
{
"origin": "agent",
"objects": {
"scooter": { "position": [1, 6], "facing": "-x" ...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "scooter": {
      "position": [
        1,
        6
      ],
      "facing": "-x"
    },
    "backpack": {
      "position": [
        3,
        5
      ],
      "facing": "+y"
    },
    "brown door": {
      "position": [
        -3,
        5
      ]
    }
  }
}

🎯 Ground Truth

{
  "backpack": {
    "position": [
      5,
      6
    ],
    "facing": "south"
  },
  "brown door": {
    "position": [
      -1,
      5
    ],
    "facing": "east"
  },
  "scooter": {
    "position": [
      1,
      6
    ],
    "facing": "east"
  }
}

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "scooter": {
      "position": [
        1,
        6
      ],
      "facing": "-x"
    },
    "backpack": {
      "position": [
        3,
        5
      ],
      "facing": "+y"
    },
    "brown door": {
      "position": [
        -3,
        5
      ]
    }
  }
}

🎯 Ground Truth

{
  "backpack": {
    "position": [
      5,
      6
    ],
    "facing": "south"
  },
  "brown door": {
    "position": [
      -1,
      5
    ],
    "facing": "east"
  },
  "scooter": {
    "position": [
      1,
      6
    ],
    "facing": "east"
  }
}

🧠 Cognitive Map Metrics

Global:

dir: 0.500

facing: 1

pos: 0.768

overall: 0.756

Global (Full):

dir: 0.275

facing: 0.667

pos: 0.563

overall: 0.502

Local:

dir: 0.500

facing: 1

pos: 0.746

overall: 0.749

Local (Newly):

dir: 0.500

facing: 1

pos: 0.746

overall: 0.749

Fog Probe:

(none)

📈 Turn Metrics

node_coverage: 0.714

edge_coverage: 0.244

is_action_fail: False

step: 5

action_counts:

move: 1

rotate: 3

return: 0

observe: 5

term: 0

forced_term: 0

query: 0

information_gain: 0.546

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 6

👤 Environment Observation (click to toggle)
You rotated counterclockwise 90°. You observe:
• scooter: front-slight-right, slightly far, facing left
• backpack: front-right, slightly far, facing forward
• brown door: front-slight-left, slightly far, on left wall.
You have a maximum of 15 exploration steps left.
Strictly follow this format:
TH...

🤔 Assistant Thinking (click to toggle)
Jump to the brown door to use the doorway vantage point to see into its connected room and quickly discover remaining unseen objects (e.g., toilet, table, chair, bike)....

💬 Assistant Action
Actions: [JumpTo(brown door), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK:
Assign integer coordinates consistent with the observed egocentric bearings/distances from the agent’s origin and subsequent doorway observations; include only observed entities with cardinal facings when provided.
FINAL ANSWER:
{
"agent": { "position": [3, -1], "facing": "south" },
"yell...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      3,
      -1
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ]
  },
  "plant": {
    "position": [
      0,
      7
    ]
  },
  "shoes": {
    "position": [
      -3,
      0
    ],
    "facing": "east"
  },
  "wine": {
    "position": [
      -2,
      0
    ]
  },
  "scooter": {
    "position": [
      -1,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -3,
      -2
    ],
    "facing": "south"
  },
  "brown door": {
    "position": [
      3,
      -1
    ]
  }
}

🎯 Ground Truth (Observed)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "south"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "south"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Current FOV from the brown door contains no visible objects or doors, so the local cognitive map has an empty objects dictionary.
FINAL ANSWER:
{"origin":"agent","objects":{}}...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {}
}

🎯 Ground Truth

(no data)

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {}
}

🎯 Ground Truth

(no data)

🌫️ Fog Probe Response (click to toggle)
THINK: The candidate points A-F all lie in regions beyond walls/doorways from the currently observed areas, primarily in the right-side rooms/corridors and upper-right area that have not been visually covered yet.
FINAL ANSWER: {
"unexplored": ["A", "B", "C", "D", "E", "F"]
}...

🗺️ Symbolic Fog Map

###############
###......######
###......######
###......######
###......######
###......######
###......######
######+########
#......########
#......#.....F#
#......#......#
#......#......#
#......*.....C#
#......#A..D..#
########EB....#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F

🤖 Predicted: A, B, C, D, E, F

🎯 Ground Truth: F, D, C

🧠 Cognitive Map Metrics

Global:

dir: 0.712

facing: 0.833

pos: 0.801

overall: 0.782

Global (Full):

dir: 0.392

facing: 0.556

pos: 0.587

overall: 0.512

Local:

(none)

Local (Newly):

(none)

Fog Probe:

precision: 0.500

recall: 1

overall: 0.667

📈 Turn Metrics

node_coverage: 0.714

edge_coverage: 0.244

is_action_fail: False

step: 6

action_counts:

move: 2

rotate: 3

return: 0

observe: 6

term: 0

forced_term: 0

query: 0

information_gain: 0.546

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 7

👤 Environment Observation (click to toggle)
You jumped to brown door. You observe: No objects in field of view..
You have a maximum of 14 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
At the brown door threshold but current facing direction likely points along the wall/out of useful view. Rotate 90° to scan into the connected room from the doorway and reveal new objects....

💬 Assistant Action
Actions: [Rotate(90), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Build a single global (origin-at-start) map using integer coordinates consistent with the observed bearings/proximities; include only observed entities and include facing for objects where it was reported.
FINAL ANSWER:
{
"agent": { "position": [4, -1], "facing": "west" },
"yellow door":...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "brown door": {
    "position": [
      4,
      -1
    ]
  },
  "television": {
    "position": [
      0,
      6
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      6
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ]
  },
  "plant": {
    "position": [
      0,
      7
    ]
  },
  "shoes": {
    "position": [
      -3,
      0
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -4,
      -1
    ]
  },
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -3,
      -2
    ],
    "facing": "south"
  }
}

🎯 Ground Truth (Observed)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "west"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "west"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Construct a local (agent-centered) map using integer coordinates consistent with the observed egocentric directions/distances and the noted proximity (shoes east and near to backpack). Include facing only where specified.
FINAL ANSWER:
{
"origin": "agent",
"objects": {
"scooter": {
...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "scooter": {
      "position": [
        -2,
        3
      ],
      "facing": "-y"
    },
    "backpack": {
      "position": [
        -1,
        5
      ],
      "facing": "-x"
    },
    "shoes": {
      "position": [
        1,
        5
      ],
      "facing": "-x"
    },
    "wine": {
      "position": [
        3,
        4
      ]
    }
  }
}

🎯 Ground Truth

{
  "wine": {
    "position": [
      3,
      5
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -1,
      6
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      1,
      6
    ],
    "facing": "south"
  },
  "scooter": {
    "position": [
      -1,
      2
    ],
    "facing": "east"
  }
}

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "scooter": {
      "position": [
        -2,
        3
      ],
      "facing": "-y"
    },
    "backpack": {
      "position": [
        -1,
        5
      ],
      "facing": "-x"
    },
    "shoes": {
      "position": [
        1,
        5
      ],
      "facing": "-x"
    },
    "wine": {
      "position": [
        3,
        4
      ]
    }
  }
}

🎯 Ground Truth

(no data)

🌫️ Fog Probe Response (click to toggle)
THINK: The entire right-side region behind the separating wall (where A, B, C, D, E, F are located) has not been observed from any viewpoint yet, so all candidate points lie in unexplored space.
FINAL ANSWER:
{
"unexplored": ["A", "B", "C", "D", "E", "F"]
}...

🗺️ Symbolic Fog Map

###############
###......######
###......######
###......######
###......######
###......######
###......######
######+########
#......########
#......#......#
#......#...D.B#
#......#......#
#......*......#
#......#CE....#
########FA....#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F

🤖 Predicted: A, B, C, D, E, F

🎯 Ground Truth: D, B, E

🧠 Cognitive Map Metrics

Global:

dir: 0.727

facing: 1

pos: 0.775

overall: 0.834

Global (Full):

dir: 0.400

facing: 0.667

pos: 0.569

overall: 0.545

Local:

dir: 0.800

facing: 1

pos: 0.828

overall: 0.876

Local (Newly):

(none)

Fog Probe:

precision: 0.500

recall: 1

overall: 0.667

📈 Turn Metrics

node_coverage: 0.714

edge_coverage: 0.341

is_action_fail: False

step: 7

action_counts:

move: 2

rotate: 4

return: 0

observe: 7

term: 0

forced_term: 0

query: 0

information_gain: 0.639

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 8

👤 Environment Observation (click to toggle)
You rotated clockwise 90°. You observe:
• scooter: front-left, mid distance, facing backward
• shoes: front-slight-right, slightly far, facing left
• backpack: front-slight-left, slightly far, facing left
• wine: front-right, slightly far
Assume your current facing direction is called "north":
• sh...

🤔 Assistant Thinking (click to toggle)
Still only seeing already-known Room 1 objects from the brown door. Rotate 180° to look through the doorway into the other connected room and search for unseen objects (toilet/table/chair/bike)....

💬 Assistant Action
Actions: [Rotate(180), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Place all observed entities on an integer grid consistent with egocentric bearings/distances across observations and jumps; convert object-facing (given relative to agent) into global cardinal facing using the agent’s facing at observation time; set current agent pose at the brown door after ...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "brown door": {
    "position": [
      2,
      -2
    ]
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ]
  },
  "plant": {
    "position": [
      0,
      7
    ]
  },
  "shoes": {
    "position": [
      -2,
      -1
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ]
  },
  "scooter": {
    "position": [
      0,
      -4
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -2,
      -3
    ],
    "facing": "south"
  },
  "table": {
    "position": [
      5,
      -4
    ]
  },
  "chair": {
    "position": [
      7,
      -4
    ],
    "facing": "south"
  },
  "toilet": {
    "position": [
      7,
      0
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  }
}

🎯 Ground Truth (Observed)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  }
}

🗺️ Local Cognitive Map Response (click to toggle)
THINK: Build a local (agent-centric) map for only the currently visible objects, placing them at integer coordinates consistent with their egocentric bearing (left/right) and distance bins; convert given facing directions into local axes (+y forward, +x right).
FINAL ANSWER:
{
"origin": "agent",
...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "chair": {
      "position": [
        1,
        5
      ],
      "facing": "+x"
    },
    "toilet": {
      "position": [
        -1,
        5
      ],
      "facing": "+y"
    },
    "table": {
      "position": [
        2,
        3
      ]
    },
    "bike": {
      "position": [
        -2,
        5
      ],
      "facing": "+y"
    }
  }
}

🎯 Ground Truth

{
  "bike": {
    "position": [
      -3,
      4
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      -1,
      6
    ],
    "facing": "east"
  },
  "chair": {
    "position": [
      1,
      4
    ],
    "facing": "south"
  },
  "table": {
    "position": [
      1,
      2
    ],
    "facing": "east"
  }
}

📊 Cognitive Map JSONs

🤖 Predicted

{
  "origin": "agent",
  "objects": {
    "chair": {
      "position": [
        1,
        5
      ],
      "facing": "+x"
    },
    "toilet": {
      "position": [
        -1,
        5
      ],
      "facing": "+y"
    },
    "table": {
      "position": [
        2,
        3
      ]
    },
    "bike": {
      "position": [
        -2,
        5
      ],
      "facing": "+y"
    }
  }
}

🎯 Ground Truth

{
  "bike": {
    "position": [
      -3,
      4
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      -1,
      6
    ],
    "facing": "east"
  },
  "chair": {
    "position": [
      1,
      4
    ],
    "facing": "south"
  },
  "table": {
    "position": [
      1,
      2
    ],
    "facing": "east"
  }
}

🌫️ Fog Probe Response (click to toggle)
THINK: From the brown-door doorway view, the central area of the connected room (around C/F/D) has been observed, but the far right/lower-right zones (around A, E, B) remain outside any prior FOV and thus are still unexplored.
FINAL ANSWER: {"unexplored":["A","B","E"]}...

🗺️ Symbolic Fog Map

###############
###......######
###......######
###......######
###......######
###......######
###......######
######+########
#......########
#......#CF....#
#......#D...A.#
#......#......#
#......*......#
#......#...EB.#
########......#
###############

🔍 Fog Probe JSONs

📍 Candidates: A, B, C, D, E, F

🤖 Predicted: A, B, E

🎯 Ground Truth: F, C, D

🧠 Cognitive Map Metrics

Global:

dir: 0.875

facing: 1

pos: 0.827

overall: 0.901

Global (Full):

dir: 0.875

facing: 1

pos: 0.827

overall: 0.901

Local:

dir: 0.600

facing: 1

pos: 0.813

overall: 0.804

Local (Newly):

dir: 0.600

facing: 1

pos: 0.813

overall: 0.804

Fog Probe:

precision: 0

recall: 0

overall: 0

📈 Turn Metrics

node_coverage: 1

edge_coverage: 0.439

is_action_fail: False

step: 8

action_counts:

move: 2

rotate: 5

return: 0

observe: 8

term: 0

forced_term: 0

query: 0

information_gain: 0.826

reward: -0.100

is_done: False

is_valid_action: True

🔄 Turn 9

👤 Environment Observation (click to toggle)
You rotated clockwise 180°. You observe:
• chair: front-slight-right, slightly far, facing right
• toilet: front-slight-left, slightly far, facing forward
• table: front-right, mid distance
• bike: front-left, slightly far, facing forward
Assume your current facing direction is called "north":
• ch...

🤔 Assistant Thinking (click to toggle)
All 12 objects and both doors have been observed, and the distribution suggests the full 3-room layout is covered (Room 1 core items; yellow door room with television/cap/basket/plant; brown door room with chair/toilet/table/bike). Further actions would be redundant cost, so terminate exploration....

💬 Assistant Action
Actions: [Term()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Need an integer-coordinate global map consistent with all observations (no Query used), anchored at initial agent origin. I’ll place doors and objects to satisfy the reported relative bearings/distances and the explicit near-relations (tv–cap; cap–basket; shoes–backpack; chair–table) as close...

📊 Cognitive Map JSONs

🤖 Predicted

{
  "agent": {
    "position": [
      3,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ]
  },
  "brown door": {
    "position": [
      3,
      -2
    ]
  },
  "television": {
    "position": [
      0,
      6
    ],
    "facing": "north"
  },
  "cap": {
    "position": [
      2,
      6
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      8
    ]
  },
  "plant": {
    "position": [
      0,
      8
    ]
  },
  "scooter": {
    "position": [
      0,
      -4
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -2,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -2,
      -1
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      2
    ]
  },
  "chair": {
    "position": [
      8,
      -4
    ],
    "facing": "south"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      6,
      -4
    ]
  },
  "bike": {
    "position": [
      7,
      1
    ],
    "facing": "east"
  }
}

🎯 Ground Truth (Observed)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  }
}

🎯 Ground Truth (Full)

{
  "scooter": {
    "position": [
      0,
      -3
    ],
    "facing": "east"
  },
  "television": {
    "position": [
      0,
      5
    ],
    "facing": "north"
  },
  "chair": {
    "position": [
      6,
      -3
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      -4,
      -1
    ],
    "facing": "south"
  },
  "cap": {
    "position": [
      2,
      5
    ],
    "facing": "east"
  },
  "toilet": {
    "position": [
      8,
      -1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -4,
      -3
    ],
    "facing": "south"
  },
  "wine": {
    "position": [
      -3,
      1
    ],
    "facing": "east"
  },
  "basket": {
    "position": [
      2,
      7
    ],
    "facing": "east"
  },
  "table": {
    "position": [
      4,
      -3
    ],
    "facing": "east"
  },
  "plant": {
    "position": [
      0,
      9
    ],
    "facing": "east"
  },
  "bike": {
    "position": [
      6,
      1
    ],
    "facing": "east"
  },
  "brown door": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      1,
      3
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      2,
      -2
    ],
    "facing": "east"
  }
}

🧠 Cognitive Map Metrics

Global:

dir: 0.858

facing: 1

pos: 0.797

overall: 0.885

Global (Full):

dir: 0.858

facing: 1

pos: 0.797

overall: 0.885

Local:

(none)

Local (Newly):

(none)

Fog Probe:

(none)

📈 Turn Metrics

node_coverage: 1

edge_coverage: 0.439

is_action_fail: False

step: 9

action_counts:

move: 2

rotate: 5

return: 0

observe: 8

term: 1

forced_term: 0

query: 0

information_gain: 0.826

reward: -0.100

is_done: True

is_valid_action: True

🔄 FB Turn 10

👤 Environment Observation (click to toggle)
You have returned to the initial position and face north.
There are 4 objects in the room that have been changed (position or orientation).
Note one object is either moved or rotated, not both.
Goal: Explore the room again and identify which objects have been changed and how with minimum costs.
Use ...

🤔 Assistant Thinking (click to toggle)
Rebuild the same key viewpoints as before with minimal Observe() calls to spot differences: first re-check from the initial position (door placement), then from the yellow door doorway (tv/cap/basket/plant cluster), then later from the brown door doorway for the remaining objects. Start with an init...

💬 Assistant Action
Actions: [Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Need to provide a complete global JSON cognitive map (agent at origin facing north) including all objects and both doors, assigning integer coordinates consistent with prior relative observations; use best-fit layout across the three rooms.
FINAL ANSWER: {
"agent": { "position": [0, 0], "fa...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Unchanged (all):

dir: 0.258

facing: 0.500

pos: 0.346

overall: 0.368

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): []

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: []

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 1

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: []

newly_observed_unchanged_objects: ['yellow door']

🔄 FB Turn 11

👤 Environment Observation (click to toggle)
You observe:
• yellow door: front-slight-right, mid distance, on front wall.
You have a maximum of 14 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
Jump to the yellow door to re-check the doorway view into the adjacent room (television/cap/basket/plant) and compare positions/orientations against the prior map....

💬 Assistant Action
Actions: [JumpTo(yellow door), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Need a consistent global integer-coordinate map (origin at initial agent position), including all objects/doors; exact coordinates weren’t queried, so provide the best-fit estimate consistent with observed bearings/distances and noted proximities.
FINAL ANSWER:
```json
{
"agent": { "positi...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Unchanged (all):

dir: 0.500

facing: 0.333

pos: 0.586

overall: 0.473

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): []

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: []

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 2

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: []

newly_observed_unchanged_objects: ['cap', 'basket']

🔄 FB Turn 12

👤 Environment Observation (click to toggle)
You jumped to yellow door. You observe:
• cap: front-right, mid distance, facing right
• basket: front-slight-right, slightly far
Assume your current facing direction is called "north":
• cap is south, near to basket.
You have a maximum of 13 exploration steps left.
Strictly follow this format:
THI...

🤔 Assistant Thinking (click to toggle)
Previously, from the yellow door facing north I could see television and plant in addition to cap/basket. Now they’re missing, so they may have moved or rotated out of view. Rotate 90° clockwise to scan an adjacent sector from the same doorway to relocate television/plant with minimal movement....

💬 Assistant Action
Actions: [Rotate(90), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Need a complete global JSON map including agent, all objects, and both doors; use a consistent integer-coordinate layout anchored at initial origin, with plausible placements consistent with observed relative relations and room connectivity.
FINAL ANSWER: {
"agent": { "position": [1, 3], "f...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Unchanged (all):

dir: 0.576

facing: 0.667

pos: 0.645

overall: 0.629

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): []

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: []

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 3

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: []

newly_observed_unchanged_objects: []

🔄 FB Turn 13

👤 Environment Observation (click to toggle)
You rotated clockwise 90°. You observe: No objects in field of view..
You have a maximum of 12 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
From the yellow-door viewpoint, television and plant are no longer visible where they previously were. Continue scanning from the same doorway by rotating to face west (180° from current east-facing) to try to reacquire them without moving....

💬 Assistant Action
Actions: [Rotate(180), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: I will output a single best-fit global grid map (integer coordinates) consistent with all observations so far, including all objects/doors and the agent; facings are given as global cardinals.
FINAL ANSWER:
```json
{
"agent": { "position": [1, 3], "facing": "west" },

"yellow door": { "p...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Changed: television:

dir: None

pos: 0.603

facing: None

overall: None

Retention: television:

dir: None

pos: 0.339

facing: None

overall: None

Unchanged (all):

dir: 0.364

facing: 1

pos: 0.276

overall: 0.547

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): ['television']

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: ['television']

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 4

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: ['television']

newly_observed_unchanged_objects: ['shoes', 'wine']

🔄 FB Turn 14

👤 Environment Observation (click to toggle)
You rotated clockwise 180°. You observe:
• television: front-left, slightly far, facing right
• shoes: front-left, slightly far, facing left
• wine: front-left, slightly far
Assume your current facing direction is called "north":
• television is west, near to shoes.
You have a maximum of 11 explora...

🤔 Assistant Thinking (click to toggle)
From the yellow door, I’ve now reacquired the television but with a different relative pose; I still need to find the missing plant and also re-check the south-facing view from this doorway (where scooter/backpack/brown door previously appeared). Rotate 90° counterclockwise to face south and observe...

💬 Assistant Action
Actions: [Rotate(-90), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: I will output a single consistent global grid map (origin at the initial start), including the agent, all objects, and both doors, using cardinal facings where available from the latest/most reliable observations.
FINAL ANSWER: {
"agent": { "position": [1, 3], "facing": "south" },
"yellow...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Changed: backpack:

dir: None

pos: None

facing: 1

overall: None

Retention: backpack:

dir: None

pos: None

facing: 0

overall: None

Unchanged (all):

dir: 0.545

facing: 1

pos: 0.725

overall: 0.757

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): ['backpack']

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: ['backpack']

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 5

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: ['backpack']

newly_observed_unchanged_objects: ['brown door', 'scooter']

🔄 FB Turn 15

👤 Environment Observation (click to toggle)
You rotated counterclockwise 90°. You observe:
• scooter: front-slight-right, slightly far, facing left
• television: front-right, slightly far, facing backward
• backpack: front-right, slightly far, facing backward
• brown door: front-slight-left, slightly far, on left wall
Assume your current fac...

🤔 Assistant Thinking (click to toggle)
To compare against the original map reliably, I should match the original viewpoint+heading at the yellow door (facing north). I’m currently facing south, so rotate 180° to face north again and observe to check whether television/plant are displaced or just out of view, and whether any orientations ...

💬 Assistant Action
Actions: [Rotate(180), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: I must output a complete global JSON map (agent, all 12 objects, 2 doors) using the initial position as origin and cardinal facings where known; with no queries available, I place integer coordinates consistent with the observed relative layout and proximity constraints.
FINAL ANSWER:
{
"a...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Unchanged (all):

dir: 0.424

facing: 1

pos: 0.624

overall: 0.683

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): []

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: []

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 6

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: []

newly_observed_unchanged_objects: []

🔄 FB Turn 16

👤 Environment Observation (click to toggle)
You rotated clockwise 180°. You observe:
• cap: front-right, mid distance, facing right
• basket: front-slight-right, slightly far
Assume your current facing direction is called "north":
• cap is south, near to basket.
You have a maximum of 9 exploration steps left.
Strictly follow this format:
THI...

🤔 Assistant Thinking (click to toggle)
We’ve already detected strong evidence of changes: television now appears in the room-1 sector near shoes/backpack (so likely a position change), and backpack’s facing differs from the baseline when viewed from the same yellow-door/south-facing viewpoint (orientation change). Next, go to the brown d...

💬 Assistant Action
Actions: [Rotate(180), JumpTo(brown door), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Construct a single globally consistent integer-coordinate map (origin at initial agent position), including all objects/doors and best-fit facings inferred from observations; unresolved items are placed plausibly to maintain room/door structure.
FINAL ANSWER:
```json
{
"agent": { "position...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Unchanged (all):

dir: 0.652

facing: 1

pos: 0.708

overall: 0.787

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): []

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: []

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 7

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: []

newly_observed_unchanged_objects: []

🔄 FB Turn 17

👤 Environment Observation (click to toggle)
You rotated clockwise 180°. You jumped to brown door. You observe: No objects in field of view..
You have a maximum of 8 exploration steps left.
Strictly follow this format:
THINK:
[Your thoughts on next step actions]
FINAL ANSWER:
Actions: [ ... ]...

🤔 Assistant Thinking (click to toggle)
At the brown door, I need to scan into both sides to compare against the baseline. First rotate 90° to re-check the Room 1 side (scooter/shoes/backpack/wine) from this doorway, then we can rotate 180° to look into the brown-door-connected room (chair/toilet/table/bike)....

💬 Assistant Action
Actions: [Rotate(90), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Need a complete global JSON including agent, all objects, and both doors; with only integer coordinates and cardinal facings where known. I’ll provide a consistent approximate map anchored at initial origin.
FINAL ANSWER:
{
"agent": { "position": [-3, 0], "facing": "north" },
"yellow door...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Unchanged (all):

dir: 0.182

facing: 0.167

pos: 0.314

overall: 0.221

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): []

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: []

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 8

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: []

newly_observed_unchanged_objects: []

🔄 FB Turn 18

👤 Environment Observation (click to toggle)
You rotated clockwise 90°. You observe:
• scooter: front-left, mid distance, facing backward
• television: front, slightly far, facing right
• shoes: front-slight-right, slightly far, facing left
• backpack: front-slight-left, slightly far, facing right
• wine: front-right, slightly far
Assume your...

🤔 Assistant Thinking (click to toggle)
From the brown door I’m currently facing into the Room-1 side (same viewpoint/heading used in the baseline). Next, rotate 180° to look through the brown door into the other connected room and re-check chair/toilet/table/bike against the baseline to find the remaining changed objects (and possibly lo...

💬 Assistant Action
Actions: [Rotate(180), Observe()]

🗺️ Global Cognitive Map Response (click to toggle)
THINK: Need a complete global JSON map (agent + 12 objects + 2 doors) using initial pose as origin; I’ll provide a consistent integer-coordinate layout matching the latest observations and proximity constraints as well as possible.
FINAL ANSWER:
{
"agent": { "position": [3, -2], "facing": "east" ...

📈 Turn Metrics

reward: -0.100

is_done: False

is_valid_action: True

🧭 False Belief Cogmap Metrics

Changed: chair:

dir: None

pos: None

facing: 1

overall: None

Retention: chair:

dir: None

pos: None

facing: 0

overall: None

Changed: plant:

dir: None

pos: 1

facing: None

overall: None

Retention: plant:

dir: None

pos: 0.188

facing: None

overall: None

Unchanged (all):

dir: 0.818

facing: 1

pos: 0.768

overall: 0.862

🧾 False Belief Object Sets

all_objects: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

all_changed_objects: ['backpack', 'chair', 'plant', 'television']

newly_observed_changed (this turn): ['chair', 'plant']

unchanged_objects: ['basket', 'bike', 'brown door', 'cap', 'scooter', 'shoes', 'table', 'toilet', 'wine', 'yellow door']

pred_changed_keys: ['chair', 'plant']

pred_unchanged_keys: ['backpack', 'basket', 'bike', 'brown door', 'cap', 'chair', 'plant', 'scooter', 'shoes', 'table', 'television', 'toilet', 'wine', 'yellow door']

🧭 False Belief Info

step: 9

correctly_identified_changes: None

f1_overall: None

f1_position: None

f1_facing: None

action_cost: None

action_cost_after_seen: None

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: []

newly_observed_changed_objects: ['chair', 'plant']

newly_observed_unchanged_objects: ['toilet', 'bike', 'table']

🔄 FB Turn 19

👤 Environment Observation (click to toggle)
You rotated clockwise 180°. You observe:
• chair: front-slight-right, slightly far, facing left
• toilet: front-slight-left, slightly far, facing forward
• table: front-right, mid distance
• plant: front-left, slightly far
• bike: front-left, slightly far, facing forward
Assume your current facing ...

🤔 Assistant Thinking (click to toggle)
Compared current observations to the baseline map: television is no longer in the yellow-door room cluster and is now co-located near shoes/backpack in room 1 → position change. Plant is no longer by the yellow door and is now near the bike in the brown-door-connected room → position change. Backpac...

💬 Assistant Action
Actions: [Term(changes="television: position, plant: position, backpack: orientation, chair: orientation")]

📈 Turn Metrics

reward: 1

is_done: True

is_valid_action: True

success: 1

🧭 False Belief Info

step: 10

correctly_identified_changes: 1

f1_overall: 1

f1_position: 1

f1_facing: 1

action_cost: 9

action_cost_after_seen: 0

ground_truth_changes: [{'name': 'chair', 'ori': True}, {'name': 'backpack', 'ori': True}, {'name': 'plant', 'pos': True}, {'name': 'television', 'pos': True}]

reported_changes: [{'name': 'television', 'pos': True}, {'name': 'plant', 'pos': True}, {'name': 'backpack', 'ori': True}, {'name': 'chair', 'ori': True}]

newly_observed_changed_objects: []

newly_observed_unchanged_objects: []

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where wine is relative to chair.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Wine is in Room 1 to the southwest of the yellow door, while chair is in the room beyond the brown door further to the east and slightly south; thus wine ends up northwest of chair at a large separation.
FINAL ANSWER:
north-west, far...

✅ Evaluation Results

id: 2a3ea1ab8ec1bd26

question: You return to your starting position and face north. From a Top-Down map, describe where wine is relative to chair. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: north west, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Evaluation state — Q1: DirectionEvaluationTask

Question 2 (ID: f7b63fa7e2d19d32)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where table is relative to television.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Table is in the room beyond the brown door (to the east/south-east of room 1), while television is beyond the yellow door (north, and more west). Combining these offsets places table to the south-east of television at an overall far distance.
FINAL ANSWER:
south-east, far...

✅ Evaluation Results

id: f7b63fa7e2d19d32

question: You return to your starting position and face north. From a Top-Down map, describe where table is relative to television. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: south east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 3 (ID: 093963cbd99a1c04)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where toilet is relative to scooter.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From the brown door viewpoint, scooter lay to the southwest while toilet lay to the northeast, so toilet is northeast of scooter; combined separation is in the far bin.
FINAL ANSWER:
north-east, far...

✅ Evaluation Results

id: 093963cbd99a1c04

question: You return to your starting position and face north. From a Top-Down map, describe where toilet is relative to scooter. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: default

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

❓ Evaluation Question (click to toggle)
Now you jump to shoes's direction, facing its direction.
Describe where backpack is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From the observation, shoes is east of backpack (near), so backpack is west of shoes. After jumping to shoes and facing the shoes’ direction (left = west), west is straight ahead.
FINAL ANSWER:
front, near...

✅ Evaluation Results

id: 3976e12c4008e19b

question: Now you jump to shoes's direction, facing its direction. Describe where backpack is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, near

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 2 (ID: c74b1f5f919fdbbc)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where basket is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From earlier relations, basket is east and north of television (northeast), and likely within a couple meters of it.
FINAL ANSWER:
front-right, near...

✅ Evaluation Results

id: c74b1f5f919fdbbc

question: Now you jump to television's direction, facing its direction. Describe where basket is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front-right, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: default

Question 3 (ID: 20fcddf7da613597)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where plant is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
At the television facing the same direction it faced (forward), the plant is slightly to the right and ahead, at a moderate distance.
FINAL ANSWER:
front-slight-right, mid distance...

✅ Evaluation Results

id: 20fcddf7da613597

question: Now you jump to television's direction, facing its direction. Describe where plant is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: default

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that basket is front-right, mid distance; plant is front, mid distance.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Basket appears to the front-right and plant straight ahead when standing at the object and facing its direction; this best matches standing at the television (which faces forward).
FINAL ANSWER:
television...

✅ Evaluation Results

id: 221e1938c962c6af

question: Now you jump to an object's position, facing its direction. You observe that basket is front-right, mid distance; plant is front, mid distance. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: television

final_pos: [5, 10]

final_ori: [0, 1]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'plant', 'direction': 'front', 'distance': 'mid distance', 'orientation': None}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 2

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: default

Question 2 (ID: b042fd780599b324)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that toilet is front-right, mid distance, facing forward.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Toilet and bike were both observed facing forward, and bike appeared further left than toilet from the same viewpoint, so from the bike (facing its direction) the toilet would fall to the front-right.
FINAL ANSWER:
bike...

✅ Evaluation Results

id: b042fd780599b324

question: Now you jump to an object's position, facing its direction. You observe that toilet is front-right, mid distance, facing forward. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: bike

final_pos: [11, 6]

final_ori: [1, 0]

final_observation: [{'name': 'toilet', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing forward'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 3

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: default

Question 3 (ID: b331cdf635e89588)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that brown door is front-left, mid distance, on front wall.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Brown door is on the east wall of Room 1 (seen “on left wall” when facing south from the yellow door). An object facing east in Room 1 would see the brown door on its front wall. Among observed objects, the scooter faces east and is in Room 1.
FINAL ANSWER:
scooter...

✅ Evaluation Results

id: b331cdf635e89588

question: Now you jump to an object's position, facing its direction. You observe that brown door is front-left, mid distance, on front wall. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: scooter

final_pos: [5, 2]

final_ori: [1, 0]

final_observation: [{'name': 'brown door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on front wall'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 1

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: default

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Jump to the object at front-slight-right, mid distance.
2. Jump to the object at front-slight-left, slightly far.
3. Rotate(90)

After executing the actions, what is the ego relation of basket rel...

🤔 Assistant Answer (click to toggle)
THINK:
After returning to start (facing north), the front-slight-right mid-distance object is the yellow door. From the yellow door (still facing north), the front-slight-left slightly-far object is the plant, so we jump to the plant. Rotating 90° makes us face east. Basket was observed slightly to ...

✅ Evaluation Results

id: 79708c6ef79fe3f2

question: You return to your starting position and face north. You will execute the following action sequence: 1. Jump to the object at front-slight-right, mid distance. 2. Jump to the object at front-slight-left, slightly far. 3. Rotate(90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-right, mid distance

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: default

Question 2 (ID: 52fe3e3f1a964c59)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(-90)
2. Jump to the object at front-slight-right, mid distance.
3. Rotate(-180)
4. Jump to the object at front-left, slightly far.
5. Rotate(-90)

After executing the actions, what is the e...

🤔 Assistant Answer (click to toggle)
THINK:
After the action sequence, I end up at the yellow door facing north; from that pose, basket was previously observed as front-slight-right at slightly far distance, so its ego relation remains that.
FINAL ANSWER:
front-slight-right, slightly far...

✅ Evaluation Results

id: 52fe3e3f1a964c59

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(-90) 2. Jump to the object at front-slight-right, mid distance. 3. Rotate(-180) 4. Jump to the object at front-left, slightly far. 5. Rotate(-90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-slight-right, slightly far

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 3 (ID: 26bdb606439e4c23)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(90)
2. Jump to the object at front-right, mid distance.
3. Jump to the object at front-right, mid distance.

After executing the actions, what is the ego relation of chair relative to you?
...

🤔 Assistant Answer (click to toggle)
THINK:
After Rotate(90) I face east. The first “front-right, mid distance” jump matches the brown door (on the east side, slightly to the right). From the brown door facing east, the “front-right, mid distance” object is the table, so I end at the table still facing east. Chair was observed near the...

✅ Evaluation Results

id: 26bdb606439e4c23

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(90) 2. Jump to the object at front-right, mid distance. 3. Jump to the object at front-right, mid distance. After executing the actions, what is the ego relation of chair relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front, near

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at...

🤔 Assistant Answer (click to toggle)
THINK:
To see scooter/shoes/wine together, the agent must be at the brown door and rotated 90° from the facing direction carried over when jumping there from the yellow door. Since JumpTo can’t be first, start with Rotate(0), then go via yellow door to get brown door into FOV, jump to it, and rotate...

✅ Evaluation Results

id: e845c6e72911adc5

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at front-right, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [7, 3]

final_ori: [-1, 0]

room_id: [1, 3]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos'], ['rotate', 180]]

final_observation: [{'name': 'scooter', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'shoes', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: True

ori_match: True

final_pos: [7.0, 3.0]

final_ori: [-1, 0]

visible_match: True

score: 1

evaluation_mode: default

Question 2 (ID: 9e96f120288b1fd3)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
basket is at front-right, mid distance

What action sequence led to this final view? The action sequence must be valid and onl...

🤔 Assistant Answer (click to toggle)
THINK:
To make basket appear front-right at mid distance, stand at television facing north; from the start, first do a non-jump move, then jump via the yellow door to the television.
FINAL ANSWER:
Rotate(0), JumpTo(yellow door), JumpTo(television)...

✅ Evaluation Results

id: 9e96f120288b1fd3

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: basket is at front-right, mid distance What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [5, 14]

final_ori: [1, 0]

room_id: 2

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'yellow door'], ['jumpto', 'plant'], ['rotate', 90]]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: False

ori_match: False

final_pos: [5.0, 10.0]

final_ori: [0, 1]

visible_match: True

score: 1

evaluation_mode: default

Question 3 (ID: 58129cad65341385)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-lef...

🤔 Assistant Answer (click to toggle)
THINK:
To get a view containing cap/basket/plant but not the television, the agent can jump onto the television’s location (so it won’t be listed), keeping the original north-facing orientation. From the start, a no-op rotation satisfies the “no JumpTo first” constraint, then jump to the yellow door...

✅ Evaluation Results

id: 58129cad65341385

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-left, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [6, 8]

final_ori: [0, 1]

room_id: [1, 2]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'initial_pos']]

final_observation: [{'name': 'cap', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'basket', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': None}, {'name': 'plant', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: False

ori_match: True

final_pos: [5.0, 10.0]

final_ori: [0, 1]

visible_match: False

score: 0

evaluation_mode: default

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: wine, chair, backpack, plant, table.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Derive a consistent integer-coordinate layout from the observed relative bearings/distances across the yellow and brown doorway viewpoints, then report the requested objects’ allocentric coordinates relative to start.
FINAL ANSWER:
(-3, 1); (7, -4); (-2, -3); (0, 7); (5, -4)...

✅ Evaluation Results

id: 77fee2388e671ed1

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: wine, chair, backpack, plant, table. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[-3, 1], [6, -3], [-4, -3], [0, 9], [4, -3]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.821

threshold: 0.900

score: 0.821

evaluation_mode: default

Question 2 (ID: 86e022f45899546e)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: table, television, backpack, toilet.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Infer a consistent integer-coordinate map from the observed qualitative bearings/distances across doorway viewpoints, anchoring the start at (0,0) and using door-jumps to triangulate approximate placements.
FINAL ANSWER:
(6, -4); (0, 6); (-2, -3); (8, 0)...

✅ Evaluation Results

id: 86e022f45899546e

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: table, television, backpack, toilet. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[4, -3], [0, 5], [-4, -3], [8, -1]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.828

threshold: 0.900

score: 0.828

evaluation_mode: default

Question 3 (ID: 5f8f2517c700a2b9)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: toilet, scooter, chair, television, plant.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Need allocentric integer coordinates relative to start; infer approximate positions from observed bearings/distances and doorway transitions.
FINAL ANSWER:
(7, -1); (-1, -2); (7, -4); (-1, 6); (0, 9)...

✅ Evaluation Results

id: 5f8f2517c700a2b9

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: toilet, scooter, chair, television, plant. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[8, -1], [0, -3], [6, -3], [0, 5], [0, 9]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.852

threshold: 0.900

score: 0.852

evaluation_mode: default

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning clockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: basket, bike, scooter, shoes, table.
List t...

🤔 Assistant Answer (click to toggle)
THINK:
Use relative room/door observations to place objects by quadrant from the start: basket is north/NE (room beyond yellow door), bike is NE/E (beyond brown door), table is SE, scooter is due south-ish, shoes are SW/W. Sort by clockwise bearing from facing north.
FINAL ANSWER:
basket, bike, tabl...

✅ Evaluation Results

id: c9f33275797c1371

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning clockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: basket, bike, scooter, shoes, table. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['basket', 'bike', 'table', 'scooter', 'shoes']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 2 (ID: 88f524a1ea9bb292)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, wine.
List them i...

🤔 Assistant Answer (click to toggle)
THINK: Reconstruct approximate object bearings from the mapped doorway observations, infer their relative coordinates to the start, convert to bearings from north, then order by encounter during counterclockwise rotation (from 0° down to -180°, then wrap).
FINAL ANSWER: wine, backpack, scooter...

✅ Evaluation Results

id: 88f524a1ea9bb292

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 3 (ID: fa85ac27ecb06dfa)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, table, wine.
List...

🤔 Assistant Answer (click to toggle)
THINK:
Infer relative bearings from the start: wine is the most west/northwest among the three Room‑1 items; backpack is west-southwest; scooter is more south-southwest. Table lies in the other room to the southeast (positive bearing), so it appears after passing south during counterclockwise rotati...

✅ Evaluation Results

id: fa85ac27ecb06dfa

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, table, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter', 'table']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

📊 Task: RotDualEvaluationTask

Question 1 (ID: b72c000118d6dabd)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You performed a complete 360° rotation in place.
Assume all walls are removed (you can see through walls), so every object is visible.
During the rotation, these objects appeared directly in front of you in this order:
basket, bike, table, scooter...

🤔 Assistant Answer (click to toggle)
THINK:
From facing north, seeing basket first and then bike/table (which are more to the right/east than basket) before reaching scooter/shoes (more left/west) indicates the view swept from north toward east, i.e., clockwise.
FINAL ANSWER:
clockwise...

✅ Evaluation Results

id: b72c000118d6dabd

question: You return to your starting position and face north. You performed a complete 360° rotation in place. Assume all walls are removed (you can see through walls), so every object is visible. During the rotation, these objects appeared directly in front of you in this order: basket, bike, table, scooter, shoes Based on this sequence, in which direction did you rotate? Answer format: clockwise or counterclockwise Example: clockwise

action: None

answer: clockwise

task_type: RotDualEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 2 (ID: 08504c64e20ddfdb)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You performed a complete 360° rotation in place.
Assume all walls are removed (you can see through walls), so every object is visible.
During the rotation, these objects appeared directly in front of you in this order:
wine, backpack, scooter

Bas...

🤔 Assistant Answer (click to toggle)
THINK:
The front-alignment order wine → backpack → scooter matches sweeping from slightly west-of-north toward more southwest (decreasing angle from 0°), which corresponds to a counterclockwise rotation.
FINAL ANSWER:
counterclockwise...

✅ Evaluation Results

id: 08504c64e20ddfdb

question: You return to your starting position and face north. You performed a complete 360° rotation in place. Assume all walls are removed (you can see through walls), so every object is visible. During the rotation, these objects appeared directly in front of you in this order: wine, backpack, scooter Based on this sequence, in which direction did you rotate? Answer format: clockwise or counterclockwise Example: clockwise

action: None

answer: counterclockwise

task_type: RotDualEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 3 (ID: 36155bdbf69a1da7)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You performed a complete 360° rotation in place.
Assume all walls are removed (you can see through walls), so every object is visible.
During the rotation, these objects appeared directly in front of you in this order:
wine, backpack, scooter, tab...

🤔 Assistant Answer (click to toggle)
THINK:
Table is in the eastern sector relative to the start while the others are in the western/southern sector, and since table appeared last in the sweep, the rotation must have gone from north toward west first.
FINAL ANSWER:
counterclockwise...

✅ Evaluation Results

id: 36155bdbf69a1da7

question: You return to your starting position and face north. You performed a complete 360° rotation in place. Assume all walls are removed (you can see through walls), so every object is visible. During the rotation, these objects appeared directly in front of you in this order: wine, backpack, scooter, table Based on this sequence, in which direction did you rotate? Answer format: clockwise or counterclockwise Example: clockwise

action: None

answer: counterclockwise

task_type: RotDualEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (1, -3) and face north.
What is the egocentric relation of wine?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From the built map, wine is at approximately (-2, 0). From the new agent pose (1, -3) facing north, wine is at vector (-3, +3), bearing -45° (front-left) and distance √18≈4.24 (slightly far).
FINAL ANSWER:
front-left, slightly far...

✅ Evaluation Results

id: efa7a1eae6c023bd

question: Still treat your initial position as origin (0, 0) You move to (1, -3) and face north. What is the egocentric relation of wine? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-left, slightly far

task_type: Action2LocationEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: default

Question 2 (ID: 29dc2089738c91f3)

❓ Evaluation Question (click to toggle)
Treat the brown door as the new 'origin' (0, 0).
You move to (5, -2) and face west.
What is the egocentric relation of chair?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Using the last known relative placement of the chair from the brown door and the new pose (5, -2) facing west, the chair falls to the forward-left at a slightly-far distance.
FINAL ANSWER:
front-left, slightly far...

✅ Evaluation Results

id: 29dc2089738c91f3

question: Treat the brown door as the new 'origin' (0, 0). You move to (5, -2) and face west. What is the egocentric relation of chair? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-right, near

task_type: Action2LocationEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: default

Question 3 (ID: 0f994784bf1c8d5b)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (-1, 0) and face west.
What is the egocentric relation of shoes?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From the new pose at (-1, 0) facing west, shoes lie in the front-right sector at a mid-range distance.
FINAL ANSWER:
front-right, mid distance...

✅ Evaluation Results

id: 0f994784bf1c8d5b

question: Still treat your initial position as origin (0, 0) You move to (-1, 0) and face west. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-slight-left, mid distance

task_type: Action2LocationEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: default

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

❓ Evaluation Question (click to toggle)
You move to a new location and face north.
You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answer forma...

🤔 Assistant Answer (click to toggle)
THINK:
Yellow door is straight ahead of the new location (same x), slightly-far; brown door is near at front-right on the right wall implying an offset of ( +1, +1 ) from the new location; choosing coordinates consistent with earlier door observations yields the new location at x=1, y=-4.
FINAL ANSW...

✅ Evaluation Results

id: 3943df1f7c7f8b07

question: You move to a new location and face north. You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [1, -3]

final_pos: [6, 2]

final_ori: [0, 1]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'wine', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': None}, {'name': 'brown door', 'direction': 'front-right', 'distance': 'near', 'orientation': 'on right wall'}, {'name': 'yellow door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: Location2ActionTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.729

raw_score: 0.729

score: 0.729

evaluation_mode: default

Question 2 (ID: f08df2fab1aea39f)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall
Treat the brown door as the new 'origin' (0, 0).
What is your new 2D coordinate (x, y)?

A...

🤔 Assistant Answer (click to toggle)
THINK:
Facing west, the brown door is front-slight-right, so the agent is east and slightly south of the door (x>0, y<0). A simple integer location consistent with “slightly far” (4–8) and a small rightward offset is (5, -1).
FINAL ANSWER:
(5, -1)...

✅ Evaluation Results

id: f08df2fab1aea39f

question: You move to a new location and face west. You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall Treat the brown door as the new 'origin' (0, 0). What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [5, -2]

final_pos: [12, 1]

final_ori: [-1, 0]

room_id: 3

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'chair', 'direction': 'front-right', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'table', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'brown door', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: Location2ActionTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.831

raw_score: 0.831

score: 0.831

evaluation_mode: default

Question 3 (ID: ce196c535efde5f3)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answe...

🤔 Assistant Answer (click to toggle)
THINK:
The observed configuration matches being located at the scooter’s position, which is at (0, -3) relative to the initial origin.
FINAL ANSWER:
(0, -3)...

✅ Evaluation Results

id: ce196c535efde5f3

question: You move to a new location and face west. You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [-1, 0]

final_pos: [4, 5]

final_ori: [-1, 0]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'shoes', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing left'}, {'name': 'backpack', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: Location2ActionTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.042

raw_score: 0.042

score: 0.042

evaluation_mode: default

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where wine is relative to chair.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a single consistent global coordinate map (origin at start, +y north) from the doorway-based relative observations, then compute wine’s cardinal direction and binned distance relative to chair using their coordinates.
FINAL ANSWER:
<cogmap>
```json
{
"agent": { "position": [5, -1]...

✅ Evaluation Results

id: 2a3ea1ab8ec1bd26

question: You return to your starting position and face north. From a Top-Down map, describe where wine is relative to chair. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: north west, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 2 (ID: f7b63fa7e2d19d32)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where table is relative to television.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a single global coordinate map consistent with observed door locations and relative bearings/distances, anchoring start at (0,0). Then compute the vector from television to table to answer cardinal direction and binned distance.
FINAL ANSWER:
<cogmap>
{
"agent": { "position": [5, ...

✅ Evaluation Results

id: f7b63fa7e2d19d32

question: You return to your starting position and face north. From a Top-Down map, describe where table is relative to television. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: south east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: 093963cbd99a1c04)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where toilet is relative to scooter.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a consistent integer-coordinate global map anchored at the start (0,0), using the observed relative bearings/distances and the near-relations to place objects; then compute the toilet’s top-down relation to the scooter from those coordinates.
FINAL ANSWER:
<cogmap>
```json
{
"agen...

✅ Evaluation Results

id: 093963cbd99a1c04

question: You return to your starting position and face north. From a Top-Down map, describe where toilet is relative to scooter. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

❓ Evaluation Question (click to toggle)
Now you jump to shoes's direction, facing its direction.
Describe where backpack is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
I must output a global cognitive map with integer coordinates (origin at the agent’s initial position). Since no Query() actions were used, I construct one consistent integer layout that satisfies the observed relative bearings/distances and the “near” constraints (e.g., television west of ca...

✅ Evaluation Results

id: 3976e12c4008e19b

question: Now you jump to shoes's direction, facing its direction. Describe where backpack is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, near

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: prompt_cogmap

Question 2 (ID: c74b1f5f919fdbbc)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where basket is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a single consistent global placement (integer grid) that matches the observed left/right/front relationships and distance bins as well as possible; then compute basket’s egocentric bearing/distance after moving to the television and facing the television’s facing direction (north).
...

✅ Evaluation Results

id: c74b1f5f919fdbbc

question: Now you jump to television's direction, facing its direction. Describe where basket is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front-right, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: 20fcddf7da613597)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where plant is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
I’ll produce a single global (integer) coordinate map consistent with the observed egocentric bearings/distances plus the given near-relations (tv west of cap; cap south of basket; shoes north of backpack in the local frame at the brown door; chair “north” of table where local north=agent-fac...

✅ Evaluation Results

id: 20fcddf7da613597

question: Now you jump to television's direction, facing its direction. Describe where plant is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: prompt_cogmap

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that basket is front-right, mid distance; plant is front, mid distance.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
As no Query() actions were used, exact coordinates aren’t uniquely determined from binned bearings/distances; I’m providing one consistent integer-coordinate global map that satisfies the observed directional/near constraints. For the final identification, the only object whose facing and rel...

✅ Evaluation Results

id: 221e1938c962c6af

question: Now you jump to an object's position, facing its direction. You observe that basket is front-right, mid distance; plant is front, mid distance. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: television

final_pos: [5, 10]

final_ori: [0, 1]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'plant', 'direction': 'front', 'distance': 'mid distance', 'orientation': None}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 2

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: prompt_cogmap

Question 2 (ID: b042fd780599b324)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that toilet is front-right, mid distance, facing forward.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
As no Query() actions were used, I build a single consistent integer-coordinate global map that satisfies the observed door connectivity (yellow door to a north room; brown door to a south room) and the key near-relations (chair near table; cap south of basket; TV west of cap). For the questi...

✅ Evaluation Results

id: b042fd780599b324

question: Now you jump to an object's position, facing its direction. You observe that toilet is front-right, mid distance, facing forward. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: bike

final_pos: [11, 6]

final_ori: [1, 0]

final_observation: [{'name': 'toilet', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing forward'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 3

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: b331cdf635e89588)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that brown door is front-left, mid distance, on front wall.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a single consistent global coordinate assignment (integer grid) matching all observed relative bearings/distances and the few given proximity constraints (tv west of cap; cap south of basket; shoes east of backpack; chair north of table). Then answer the identification question by c...

✅ Evaluation Results

id: b331cdf635e89588

question: Now you jump to an object's position, facing its direction. You observe that brown door is front-left, mid distance, on front wall. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: scooter

final_pos: [5, 2]

final_ori: [1, 0]

final_observation: [{'name': 'brown door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on front wall'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 1

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: prompt_cogmap

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Jump to the object at front-slight-right, mid distance.
2. Jump to the object at front-slight-left, slightly far.
3. Rotate(90)

After executing the actions, what is the ego relation of basket rel...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a globally consistent integer-coordinate map using the initial position as (0,0) and the observed relative relations to place doors/objects. Then simulate the given jump/jump/rotate sequence to compute basket’s egocentric relation from the final pose.
FINAL ANSWER:
<cogmap>
```json
...

✅ Evaluation Results

id: 79708c6ef79fe3f2

question: You return to your starting position and face north. You will execute the following action sequence: 1. Jump to the object at front-slight-right, mid distance. 2. Jump to the object at front-slight-left, slightly far. 3. Rotate(90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-right, mid distance

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: prompt_cogmap

Question 2 (ID: 52fe3e3f1a964c59)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(-90)
2. Jump to the object at front-slight-right, mid distance.
3. Rotate(-180)
4. Jump to the object at front-left, slightly far.
5. Rotate(-90)

After executing the actions, what is the e...

🤔 Assistant Answer (click to toggle)
THINK:
Assign consistent integer coordinates satisfying all observed qualitative (binned) egocentric relations and the given close-object constraints. Then simulate the provided rotate/jump sequence from the start pose to determine the final pose and compute basket’s egocentric direction/distance bi...

✅ Evaluation Results

id: 52fe3e3f1a964c59

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(-90) 2. Jump to the object at front-slight-right, mid distance. 3. Rotate(-180) 4. Jump to the object at front-left, slightly far. 5. Rotate(-90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-slight-right, slightly far

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: 26bdb606439e4c23)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(90)
2. Jump to the object at front-right, mid distance.
3. Jump to the object at front-right, mid distance.

After executing the actions, what is the ego relation of chair relative to you?
...

🤔 Assistant Answer (click to toggle)
THINK:
I’ll construct a single global coordinate map (integer grid) consistent with the observed bearings/distances and the noted close-object relations (e.g., television west of cap; cap south of basket; shoes east of backpack; chair near table). Then I’ll simulate the given action sequence from th...

✅ Evaluation Results

id: 26bdb606439e4c23

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(90) 2. Jump to the object at front-right, mid distance. 3. Jump to the object at front-right, mid distance. After executing the actions, what is the ego relation of chair relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front, near

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: prompt_cogmap

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at...

🤔 Assistant Answer (click to toggle)
THINK:
Assemble a single global grid using the start as (0,0), choosing integer coordinates consistent with the observed angle/distance bins and the given near-relations (tv–cap, cap–basket, chair–table, shoes–backpack). Then, for the action sequence, recreate the viewpoint where scooter/shoes/wine ...

✅ Evaluation Results

id: e845c6e72911adc5

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at front-right, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [7, 3]

final_ori: [-1, 0]

room_id: [1, 3]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos'], ['rotate', 180]]

final_observation: [{'name': 'scooter', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'shoes', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: True

ori_match: True

final_pos: [7.0, 3.0]

final_ori: [-1, 0]

visible_match: True

score: 1

evaluation_mode: prompt_cogmap

Question 2 (ID: 9e96f120288b1fd3)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
basket is at front-right, mid distance

What action sequence led to this final view? The action sequence must be valid and onl...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a single consistent global integer-coordinate layout that matches the observed door locations and the qualitative (binned) relative relations. For the final-view question, start from origin facing north, use a non-jump first move, then jump via the only initially-visible door (yello...

✅ Evaluation Results

id: 9e96f120288b1fd3

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: basket is at front-right, mid distance What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [5, 14]

final_ori: [1, 0]

room_id: 2

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'yellow door'], ['jumpto', 'plant'], ['rotate', 90]]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: False

ori_match: False

final_pos: [5.0, 10.0]

final_ori: [0, 1]

visible_match: True

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: 58129cad65341385)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-lef...

🤔 Assistant Answer (click to toggle)
THINK:
We never used Query(), so exact coordinates aren’t uniquely determined; I’ll provide one integer-coordinate global map consistent with the observed bearings/proximities and door connectivity.
For the second part, the described final view matches what was seen when standing at the yellow doo...

✅ Evaluation Results

id: 58129cad65341385

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-left, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [6, 8]

final_ori: [0, 1]

room_id: [1, 2]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'initial_pos']]

final_observation: [{'name': 'cap', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'basket', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': None}, {'name': 'plant', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: True

ori_match: True

final_pos: [6.0, 8.0]

final_ori: [0, 1]

visible_match: True

score: 1

evaluation_mode: prompt_cogmap

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: wine, chair, backpack, plant, table.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
No Query() actions were used, so exact coordinates aren’t directly given; I’m constructing a single consistent integer-grid placement that satisfies all observed egocentric bearings, distance bins, doorway jumps, and the reported near-relations (television–cap; cap–basket; shoes–backpack; cha...

✅ Evaluation Results

id: 77fee2388e671ed1

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: wine, chair, backpack, plant, table. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[-3, 1], [6, -3], [-4, -3], [0, 9], [4, -3]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.673

threshold: 0.900

score: 0.673

evaluation_mode: prompt_cogmap

Question 2 (ID: 86e022f45899546e)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: table, television, backpack, toilet.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Construct a single consistent global placement (integer grid) that matches the observed doorway-centric layout and the strongest relative constraints; then read off allocentric coordinates for the requested objects.
FINAL ANSWER:
<cogmap>
{
"agent": { "position": [0, -2], "facing": "east" }...

✅ Evaluation Results

id: 86e022f45899546e

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: table, television, backpack, toilet. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[4, -3], [0, 5], [-4, -3], [8, -1]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.299

threshold: 0.900

score: 0.299

evaluation_mode: prompt_cogmap

Question 3 (ID: 5f8f2517c700a2b9)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: toilet, scooter, chair, television, plant.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
I’ll produce a single consistent integer-coordinate global map anchored at the start (0,0), using the observed left/right/front relations plus the given proximity constraints (tv near cap; cap south of basket near; shoes east-of backpack (in the local frame) interpreted as shoes north of back...

✅ Evaluation Results

id: 5f8f2517c700a2b9

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: toilet, scooter, chair, television, plant. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[8, -1], [0, -3], [6, -3], [0, 5], [0, 9]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.805

threshold: 0.900

score: 0.805

evaluation_mode: prompt_cogmap

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning clockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: basket, bike, scooter, shoes, table.
List t...

🤔 Assistant Answer (click to toggle)
THINK:
Assemble a single consistent global coordinate assignment (integer grid) for all observed objects/doors relative to the start (0,0), using the sequence of doorway-based observations to place items into three connected areas. Then, for the rotation question, compute each target object’s bearin...

✅ Evaluation Results

id: c9f33275797c1371

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning clockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: basket, bike, scooter, shoes, table. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['basket', 'bike', 'table', 'scooter', 'shoes']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 2 (ID: 88f524a1ea9bb292)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, wine.
List them i...

🤔 Assistant Answer (click to toggle)
THINK:
I will construct a single global coordinate map (integer grid) consistent with all observed relative bearings/distances and the stated “near” relations, using your initial start as (0,0) and north as +y. Then I’ll compute the bearings from (0,0) to backpack/scooter/wine; during a continuous c...

✅ Evaluation Results

id: 88f524a1ea9bb292

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: fa85ac27ecb06dfa)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, table, wine.
List...

🤔 Assistant Answer (click to toggle)
THINK:
I need integer coordinates in the global frame (origin at the initial agent position, +y = north). Since no Query() actions were used, I’m constructing a single consistent coordinate assignment that matches the observed relative bearings/distances and the local proximity constraints (tv near ...

✅ Evaluation Results

id: fa85ac27ecb06dfa

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, table, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter', 'table']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (1, -3) and face north.
What is the egocentric relation of wine?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
I need to output an integer-coordinate global cognitive map (origin at the agent start), using only observed entities. Since no Query() actions were used, I construct a single consistent placement that satisfies the observed left/right/front relations and the “near” constraints (≤2) that were...

✅ Evaluation Results

id: efa7a1eae6c023bd

question: Still treat your initial position as origin (0, 0) You move to (1, -3) and face north. What is the egocentric relation of wine? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-left, slightly far

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: prompt_cogmap

Question 2 (ID: 29dc2089738c91f3)

❓ Evaluation Question (click to toggle)
Treat the brown door as the new 'origin' (0, 0).
You move to (5, -2) and face west.
What is the egocentric relation of chair?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
I must output a single consistent global map (integer coordinates) using the initial agent position as (0,0), facing north. Since no Query() actions were used, exact coordinates are underdetermined; I’ll provide one self-consistent integer placement that matches the observed relative bearings...

✅ Evaluation Results

id: 29dc2089738c91f3

question: Treat the brown door as the new 'origin' (0, 0). You move to (5, -2) and face west. What is the egocentric relation of chair? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-right, near

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: prompt_cogmap

Question 3 (ID: 0f994784bf1c8d5b)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (-1, 0) and face west.
What is the egocentric relation of shoes?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
We never used Query(), so exact coordinates aren’t uniquely determined; I’ll provide one consistent integer-coordinate global map that satisfies all observed left/right/front and “near” constraints. Then compute shoes’ egocentric relation from the new agent pose at (-1,0) facing west: shoes a...

✅ Evaluation Results

id: 0f994784bf1c8d5b

question: Still treat your initial position as origin (0, 0) You move to (-1, 0) and face west. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-slight-left, mid distance

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: prompt_cogmap

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

❓ Evaluation Question (click to toggle)
You move to a new location and face north.
You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answer forma...

🤔 Assistant Answer (click to toggle)
THINK:
I need to provide a single consistent global (integer) coordinate map using the initial position as (0,0), with all observed objects/doors. Since we never used Query(), exact coordinates are underdetermined; I’ll give a coherent integer layout consistent with the observed relative bearings/di...

✅ Evaluation Results

id: 3943df1f7c7f8b07

question: You move to a new location and face north. You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [1, -3]

final_pos: [6, 2]

final_ori: [0, 1]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'wine', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': None}, {'name': 'brown door', 'direction': 'front-right', 'distance': 'near', 'orientation': 'on right wall'}, {'name': 'yellow door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.729

raw_score: 0.729

score: 0.729

evaluation_mode: prompt_cogmap

Question 2 (ID: f08df2fab1aea39f)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall
Treat the brown door as the new 'origin' (0, 0).
What is your new 2D coordinate (x, y)?

A...

🤔 Assistant Answer (click to toggle)
THINK:
I’ll build a single consistent global integer-coordinate map using the initial agent pose as origin (0,0), north = +y. Distances were only binned, so positions are chosen to satisfy all observed qualitative relations (left/right/front, near/mid/slightly-far) and the stated near-relations.
For...

✅ Evaluation Results

id: f08df2fab1aea39f

question: You move to a new location and face west. You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall Treat the brown door as the new 'origin' (0, 0). What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [5, -2]

final_pos: [12, 1]

final_ori: [-1, 0]

room_id: 3

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'chair', 'direction': 'front-right', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'table', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'brown door', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.769

raw_score: 0.769

score: 0.769

evaluation_mode: prompt_cogmap

Question 3 (ID: ce196c535efde5f3)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answe...

🤔 Assistant Answer (click to toggle)
THINK:
I’ll build a single consistent global (x,y) map using the initial position as (0,0), based on the observed door jumps and relative bearings/distances (with integer placements that satisfy the key constraints, especially the later localization). Then, for the new location: facing west, use the...

✅ Evaluation Results

id: ce196c535efde5f3

question: You move to a new location and face west. You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [-1, 0]

final_pos: [4, 5]

final_ori: [-1, 0]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'shoes', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing left'}, {'name': 'backpack', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.107

raw_score: 0.107

score: 0.107

evaluation_mode: prompt_cogmap

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where wine is relative to chair.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Compute wine position relative to chair: from chair (6,-3) to wine (-3,1) is 9 units west and 4 units north, which is north-west; distance √97 ≈ 9.85 falls in the (8,16] bin = far.
FINAL ANSWER:
north-west, far...

✅ Evaluation Results

id: 2a3ea1ab8ec1bd26

question: You return to your starting position and face north. From a Top-Down map, describe where wine is relative to chair. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: north west, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: f7b63fa7e2d19d32)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where table is relative to television.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Compute vector from television (0,5) to table (4,-3): (4,-8) → south-east; distance √80 ≈ 8.94 → far.
FINAL ANSWER:
south-east, far...

✅ Evaluation Results

id: f7b63fa7e2d19d32

question: You return to your starting position and face north. From a Top-Down map, describe where table is relative to television. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: south east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: 093963cbd99a1c04)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where toilet is relative to scooter.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Compute vector from scooter (0,-3) to toilet (8,-1): (dx=+8, dy=+2) → direction falls in east bin; distance √(8²+2²)=√68≈8.25 → far.
FINAL ANSWER:
east, far...

✅ Evaluation Results

id: 093963cbd99a1c04

question: You return to your starting position and face north. From a Top-Down map, describe where toilet is relative to scooter. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

❓ Evaluation Question (click to toggle)
Now you jump to shoes's direction, facing its direction.
Describe where backpack is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
At shoes (-4,-1) facing south, backpack (-4,-3) is 2 units straight ahead (south).
FINAL ANSWER:
front, near...

✅ Evaluation Results

id: 3976e12c4008e19b

question: Now you jump to shoes's direction, facing its direction. Describe where backpack is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, near

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: c74b1f5f919fdbbc)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where basket is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From television at (0,5) facing north, basket at (2,7) is 2 right and 2 forward; angle 45° and distance √8≈2.83.
FINAL ANSWER:
front-right, mid distance...

✅ Evaluation Results

id: c74b1f5f919fdbbc

question: Now you jump to television's direction, facing its direction. Describe where basket is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front-right, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: 20fcddf7da613597)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where plant is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Agent is at television (0,5) facing north; plant at (0,9) is directly ahead by 4 units, which bins to mid distance.
FINAL ANSWER:
front, mid distance...

✅ Evaluation Results

id: 20fcddf7da613597

question: Now you jump to television's direction, facing its direction. Describe where plant is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that basket is front-right, mid distance; plant is front, mid distance.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
From television (0,5) facing north, basket at (2,7) is at a 45° front-right direction and √8≈2.83 (mid). Plant at (0,9) is straight ahead (front) at distance 4 (mid). This matches the observation.
FINAL ANSWER:
television...

✅ Evaluation Results

id: 221e1938c962c6af

question: Now you jump to an object's position, facing its direction. You observe that basket is front-right, mid distance; plant is front, mid distance. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: television

final_pos: [5, 10]

final_ori: [0, 1]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'plant', 'direction': 'front', 'distance': 'mid distance', 'orientation': None}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 2

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: b042fd780599b324)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that toilet is front-right, mid distance, facing forward.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Toilet is at (8,-1) facing east. Since it appears “facing forward,” I must be facing east too. From the bike at (6,1) facing east, the vector to the toilet is (2,-2): front-right at 45° and distance √8 ≈ 2.83 (mid).
FINAL ANSWER:
bike...

✅ Evaluation Results

id: b042fd780599b324

question: Now you jump to an object's position, facing its direction. You observe that toilet is front-right, mid distance, facing forward. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: bike

final_pos: [11, 6]

final_ori: [1, 0]

final_observation: [{'name': 'toilet', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing forward'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 3

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: b331cdf635e89588)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that brown door is front-left, mid distance, on front wall.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Check which object’s position (and its facing direction) would make the brown door appear in the front-left at a mid (2–4) distance. From scooter at (0,-3) facing east, the vector to the brown door at (2,-2) is (2,1), which is ~26.6° to the left of facing direction and distance ~2.24 → matche...

✅ Evaluation Results

id: b331cdf635e89588

question: Now you jump to an object's position, facing its direction. You observe that brown door is front-left, mid distance, on front wall. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: scooter

final_pos: [5, 2]

final_ori: [1, 0]

final_observation: [{'name': 'brown door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on front wall'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 1

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Jump to the object at front-slight-right, mid distance.
2. Jump to the object at front-slight-left, slightly far.
3. Rotate(90)

After executing the actions, what is the ego relation of basket rel...

🤔 Assistant Answer (click to toggle)
THINK:
Track jumps using the described ego relations, then compute basket’s position relative to the final agent pose (at plant, facing east) to get bearing bin and distance bin.
FINAL ANSWER:
front-right, mid distance...

✅ Evaluation Results

id: 79708c6ef79fe3f2

question: You return to your starting position and face north. You will execute the following action sequence: 1. Jump to the object at front-slight-right, mid distance. 2. Jump to the object at front-slight-left, slightly far. 3. Rotate(90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-right, mid distance

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: 52fe3e3f1a964c59)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(-90)
2. Jump to the object at front-slight-right, mid distance.
3. Rotate(-180)
4. Jump to the object at front-left, slightly far.
5. Rotate(-90)

After executing the actions, what is the e...

🤔 Assistant Answer (click to toggle)
THINK:
Simulate the action sequence from the start pose using the given coordinates to find the final agent pose, then compute the basket’s bearing/distance from that pose and bin them into the required ego direction and distance labels.
FINAL ANSWER:
front-slight-right, slightly far...

✅ Evaluation Results

id: 52fe3e3f1a964c59

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(-90) 2. Jump to the object at front-slight-right, mid distance. 3. Rotate(-180) 4. Jump to the object at front-left, slightly far. 5. Rotate(-90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-slight-right, slightly far

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: 26bdb606439e4c23)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(90)
2. Jump to the object at front-right, mid distance.
3. Jump to the object at front-right, mid distance.

After executing the actions, what is the ego relation of chair relative to you?
...

🤔 Assistant Answer (click to toggle)
THINK:
After rotating to face east, the first front-right mid-distance object is the brown door (2,-2). From there, the next front-right mid-distance object is the table (4,-3). At the table facing east, the chair at (6,-3) is directly in front at distance 2.
FINAL ANSWER:
front, near...

✅ Evaluation Results

id: 26bdb606439e4c23

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(90) 2. Jump to the object at front-right, mid distance. 3. Jump to the object at front-right, mid distance. After executing the actions, what is the ego relation of chair relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front, near

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at...

🤔 Assistant Answer (click to toggle)
THINK:
The observed configuration matches being located at the brown door’s coordinates (2,-2) while facing west. From the start (0,0) facing north, rotate to face south so the brown door enters FOV, jump to it, then rotate to face west.
FINAL ANSWER:
Rotate(180), JumpTo(brown door), Rotate(90)...

✅ Evaluation Results

id: e845c6e72911adc5

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at front-right, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [7, 3]

final_ori: [-1, 0]

room_id: [1, 3]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos'], ['rotate', 180]]

final_observation: [{'name': 'scooter', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'shoes', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: True

ori_match: True

final_pos: [7.0, 3.0]

final_ori: [-1, 0]

visible_match: True

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: 9e96f120288b1fd3)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
basket is at front-right, mid distance

What action sequence led to this final view? The action sequence must be valid and onl...

🤔 Assistant Answer (click to toggle)
THINK:
We need a move-only sequence from the reset start (0,0) facing north to a pose where the basket appears front-right at mid distance. Jumping onto the plant at (0,9) and facing east makes the basket at (2,7) lie 45° to the right at distance √8 (mid). Since JumpTo can’t be the first action, rot...

✅ Evaluation Results

id: 9e96f120288b1fd3

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: basket is at front-right, mid distance What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [5, 14]

final_ori: [1, 0]

room_id: 2

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'yellow door'], ['jumpto', 'plant'], ['rotate', 90]]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

error: target_not_visible

score: 0

evaluation_mode: use_gt_cogmap

Question 3 (ID: 58129cad65341385)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-lef...

🤔 Assistant Answer (click to toggle)
THINK:
To end up seeing the cap/basket/plant cluster with the correct bearings/distances, the agent must be standing at the yellow door while still facing north. Since a JumpTo action cannot be the first move, do a no-op rotation first, then jump.
FINAL ANSWER:
Rotate(0), JumpTo(yellow door)...

✅ Evaluation Results

id: 58129cad65341385

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-left, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [6, 8]

final_ori: [0, 1]

room_id: [1, 2]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'initial_pos']]

final_observation: [{'name': 'cap', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'basket', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': None}, {'name': 'plant', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: True

ori_match: True

final_pos: [6.0, 8.0]

final_ori: [0, 1]

visible_match: True

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: wine, chair, backpack, plant, table.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Use the provided reference cognitive map coordinates and list them in the requested object order.
FINAL ANSWER:
(-3, 1); (6, -3); (-4, -3); (0, 9); (4, -3)...

✅ Evaluation Results

id: 77fee2388e671ed1

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: wine, chair, backpack, plant, table. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[-3, 1], [6, -3], [-4, -3], [0, 9], [4, -3]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 1

threshold: 0.900

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: 86e022f45899546e)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: table, television, backpack, toilet.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Use the provided reference cognitive map coordinates and report them in the requested object order.
FINAL ANSWER:
(4, -3); (0, 5); (-4, -3); (8, -1)...

✅ Evaluation Results

id: 86e022f45899546e

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: table, television, backpack, toilet. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[4, -3], [0, 5], [-4, -3], [8, -1]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 1

threshold: 0.900

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: 5f8f2517c700a2b9)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: toilet, scooter, chair, television, plant.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Use the provided reference cognitive map coordinates and list them in the requested object order.
FINAL ANSWER:
(8, -1); (0, -3); (6, -3); (0, 5); (0, 9)...

✅ Evaluation Results

id: 5f8f2517c700a2b9

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: toilet, scooter, chair, television, plant. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[8, -1], [0, -3], [6, -3], [0, 5], [0, 9]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 1

threshold: 0.900

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning clockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: basket, bike, scooter, shoes, table.
List t...

🤔 Assistant Answer (click to toggle)
THINK:
Compute each object’s clockwise bearing from north using angle = atan2(x, y) in degrees, map to [0,360), then sort ascending (tie-break by nearer distance).
FINAL ANSWER:
basket, bike, table, scooter, shoes...

✅ Evaluation Results

id: c9f33275797c1371

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning clockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: basket, bike, scooter, shoes, table. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['basket', 'bike', 'table', 'scooter', 'shoes']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: 88f524a1ea9bb292)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, wine.
List them i...

🤔 Assistant Answer (click to toggle)
THINK:
Compute bearings from agent (0,0): wine ≈ -71.6°, backpack ≈ -126.9°, scooter = -180°. During continuous counterclockwise rotation from 0° down to -360°, these are encountered in that order.
FINAL ANSWER:
wine, backpack, scooter...

✅ Evaluation Results

id: 88f524a1ea9bb292

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: fa85ac27ecb06dfa)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, table, wine.
List...

🤔 Assistant Answer (click to toggle)
THINK:
Compute each object’s bearing from the origin (0° = north, + clockwise). During continuous counterclockwise rotation from 0° through -180° to -360° (≡ +180° to 0°), the objects align straight ahead in this sequence of bearings: wine (-71.6°), backpack (-126.9°), scooter (±180°), table (+126.9...

✅ Evaluation Results

id: fa85ac27ecb06dfa

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, table, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter', 'table']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (1, -3) and face north.
What is the egocentric relation of wine?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From (1,-3) to wine (-3,1) is (-4,+4): 45° to the left of forward and distance √32 ≈ 5.7, which bins to slightly far.
FINAL ANSWER:
front-left, slightly far...

✅ Evaluation Results

id: efa7a1eae6c023bd

question: Still treat your initial position as origin (0, 0) You move to (1, -3) and face north. What is the egocentric relation of wine? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-left, slightly far

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: 29dc2089738c91f3)

❓ Evaluation Question (click to toggle)
Treat the brown door as the new 'origin' (0, 0).
You move to (5, -2) and face west.
What is the egocentric relation of chair?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Convert chair to brown-door-centered coords, then compute chair’s vector relative to agent at (5,-2) facing west; map bearing to egocentric bin and distance to bin.
FINAL ANSWER:
front-right, near...

✅ Evaluation Results

id: 29dc2089738c91f3

question: Treat the brown door as the new 'origin' (0, 0). You move to (5, -2) and face west. What is the egocentric relation of chair? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-right, near

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: 0f994784bf1c8d5b)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (-1, 0) and face west.
What is the egocentric relation of shoes?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Agent at (-1,0) facing west; shoes at (-4,-1) gives vector (-3,-1). Relative to west-facing frame this is mostly forward with slight left offset; distance is ~3.16 which is mid.
FINAL ANSWER:
front-slight-left, mid distance...

✅ Evaluation Results

id: 0f994784bf1c8d5b

question: Still treat your initial position as origin (0, 0) You move to (-1, 0) and face west. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-slight-left, mid distance

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

❓ Evaluation Question (click to toggle)
You move to a new location and face north.
You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answer forma...

🤔 Assistant Answer (click to toggle)
THINK:
Use the given object coordinates. “Yellow door” is observed at “front”, so agent shares its x-coordinate (x=1) and is south of it. The yellow-door distance is “slightly far” (4–8), so |3−y| ∈ (4,8] ⇒ y ∈ {−5,−4,−3,−2,−1}. “Brown door” is “near” to the agent: distance to (2,−2) must be ≤2; wit...

✅ Evaluation Results

id: 3943df1f7c7f8b07

question: You move to a new location and face north. You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [1, -3]

final_pos: [6, 2]

final_ori: [0, 1]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'wine', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': None}, {'name': 'brown door', 'direction': 'front-right', 'distance': 'near', 'orientation': 'on right wall'}, {'name': 'yellow door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 1

raw_score: 1

score: 1

evaluation_mode: use_gt_cogmap

Question 2 (ID: f08df2fab1aea39f)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall
Treat the brown door as the new 'origin' (0, 0).
What is your new 2D coordinate (x, y)?

A...

🤔 Assistant Answer (click to toggle)
THINK:
From the observation while facing west, the only integer location consistent with chair being front-right and near, and with table and brown door at the given relative bearings/distances, is agent at global (7, -4). Relative to the brown door at (2, -2), the agent is offset by (7-2, -4-(-2)) ...

✅ Evaluation Results

id: f08df2fab1aea39f

question: You move to a new location and face west. You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall Treat the brown door as the new 'origin' (0, 0). What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [5, -2]

final_pos: [12, 1]

final_ori: [-1, 0]

room_id: 3

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'chair', 'direction': 'front-right', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'table', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'brown door', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 1

raw_score: 1

score: 1

evaluation_mode: use_gt_cogmap

Question 3 (ID: ce196c535efde5f3)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answe...

🤔 Assistant Answer (click to toggle)
THINK:
Facing west means “front” is toward negative x. The observed angle bins imply the agent is east of shoes/backpack/wine, with y between -1 and 1, and specifically y≠-1 (else shoes would be exactly front). Testing integer candidates with the distance bins, (x, y)=(-1, 0) satisfies all three obj...

✅ Evaluation Results

id: ce196c535efde5f3

question: You move to a new location and face west. You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [-1, 0]

final_pos: [4, 5]

final_ori: [-1, 0]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'shoes', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing left'}, {'name': 'backpack', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 1

raw_score: 1

score: 1

evaluation_mode: use_gt_cogmap

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where wine is relative to chair.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Using the top-down coordinates: chair at (8, -4) and wine at (-3, 2). From chair to wine is 11 units west and 6 units north → northwest direction; distance √157 ≈ 12.5 → far.
FINAL ANSWER:
north-west, far...

✅ Evaluation Results

id: 2a3ea1ab8ec1bd26

question: You return to your starting position and face north. From a Top-Down map, describe where wine is relative to chair. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: north west, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 2 (ID: f7b63fa7e2d19d32)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where table is relative to television.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK: Using the global coordinates: television at (0,6), table at (6,-4). Table is 6 east and 10 south of television → south-east; distance √(6²+10²)≈11.7 → far.
FINAL ANSWER:
south-east, far...

✅ Evaluation Results

id: f7b63fa7e2d19d32

question: You return to your starting position and face north. From a Top-Down map, describe where table is relative to television. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: south east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 3 (ID: 093963cbd99a1c04)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
From a Top-Down map, describe where toilet is relative to scooter.
Answer format: <cardinal direction>, <distance>
Example: north-west, near
...

🤔 Assistant Answer (click to toggle)
THINK:
Use the mapped coordinates: scooter at (0,-4), toilet at (8,-1). Toilet is 8 units east and 3 units north of scooter; angle falls in the “east” bin and distance ≈8.54 falls in “far”.
FINAL ANSWER:
east, far...

✅ Evaluation Results

id: 093963cbd99a1c04

question: You return to your starting position and face north. From a Top-Down map, describe where toilet is relative to scooter. Answer format: <cardinal direction>, <distance> Example: north-west, near

action: None

answer: east, far

task_type: DirectionEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

❓ Evaluation Question (click to toggle)
Now you jump to shoes's direction, facing its direction.
Describe where backpack is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK: At shoes position facing south, backpack is 2 units straight ahead (south), which is front and in the near distance bin.
FINAL ANSWER:
front, near...

✅ Evaluation Results

id: 3976e12c4008e19b

question: Now you jump to shoes's direction, facing its direction. Describe where backpack is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, near

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 2 (ID: c74b1f5f919fdbbc)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where basket is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
After jumping, I am at the television and facing north. Basket is 2 units right and 2 units forward from me: bearing 45° (front-right) and distance √8 ≈ 2.83 (mid distance).
FINAL ANSWER:
front-right, mid distance...

✅ Evaluation Results

id: c74b1f5f919fdbbc

question: Now you jump to television's direction, facing its direction. Describe where basket is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front-right, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 3 (ID: 20fcddf7da613597)

❓ Evaluation Question (click to toggle)
Now you jump to television's direction, facing its direction.
Describe where plant is relative to you.
Answer format: <ego direction>, <distance>
Example: front-left, near
...

🤔 Assistant Answer (click to toggle)
THINK:
After jumping to the television, I’m at the television’s position and facing the television’s facing direction (north). The plant is 2 units directly ahead.
FINAL ANSWER:
front, near...

✅ Evaluation Results

id: 20fcddf7da613597

question: Now you jump to television's direction, facing its direction. Describe where plant is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near

action: None

answer: front, mid distance

task_type: PovEvaluationTask

choices: []

kwargs:

(none)

score: 0.500

evaluation_mode: use_model_cogmap

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that basket is front-right, mid distance; plant is front, mid distance.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Basket is known to be north of (and near) the cap, and the cap is east (and near) the television, placing the basket roughly northeast of the television at a mid-range possible distance. If I’m standing at the television facing its direction (north), the basket would appear front-right and th...

✅ Evaluation Results

id: 221e1938c962c6af

question: Now you jump to an object's position, facing its direction. You observe that basket is front-right, mid distance; plant is front, mid distance. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: television

final_pos: [5, 10]

final_ori: [0, 1]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'plant', 'direction': 'front', 'distance': 'mid distance', 'orientation': None}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 2

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: use_model_cogmap

Question 2 (ID: b042fd780599b324)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that toilet is front-right, mid distance, facing forward.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
“Toilet … facing forward” means my current facing matches the toilet’s facing (east). Among observed objects that face east, the only one plausibly within mid distance (2–4) of the toilet in the same room is the bike (cap and scooter are in other rooms and would be farther). From the bike fac...

✅ Evaluation Results

id: b042fd780599b324

question: Now you jump to an object's position, facing its direction. You observe that toilet is front-right, mid distance, facing forward. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: bike

final_pos: [11, 6]

final_ori: [1, 0]

final_observation: [{'name': 'toilet', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing forward'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 3

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: use_model_cogmap

Question 3 (ID: b331cdf635e89588)

❓ Evaluation Question (click to toggle)
Now you jump to an object's position, facing its direction.
You observe that brown door is front-left, mid distance, on front wall.
Which object are you standing at?
Answer format: <object_name>
Example: lamp
...

🤔 Assistant Answer (click to toggle)
THINK:
Brown door being on the “front wall” implies I’m facing toward the wall the brown door is on; among observed objects with a facing direction, the scooter is the one plausibly facing toward the brown door’s wall such that the door appears front-left at mid distance.
FINAL ANSWER:
scooter...

✅ Evaluation Results

id: b331cdf635e89588

question: Now you jump to an object's position, facing its direction. You observe that brown door is front-left, mid distance, on front wall. Which object are you standing at? Answer format: <object_name> Example: lamp

action: None

answer:

answer: scooter

final_pos: [5, 2]

final_ori: [1, 0]

final_observation: [{'name': 'brown door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on front wall'}]

object_positions:

scooter: [5.0, 2.0]

television: [5.0, 10.0]

chair: [11.0, 2.0]

shoes: [1.0, 4.0]

cap: [7.0, 10.0]

toilet: [13.0, 4.0]

backpack: [1.0, 2.0]

wine: [2.0, 6.0]

basket: [7.0, 12.0]

table: [9.0, 2.0]

plant: [5.0, 14.0]

bike: [11.0, 6.0]

brown door: [7.0, 3.0]

yellow door: [6.0, 8.0]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

room_id: 1

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: BackwardPovTextEvaluationTask

choices: []

kwargs:

(none)

name_match: True

view_match: True

score: 1

evaluation_mode: use_model_cogmap

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Jump to the object at front-slight-right, mid distance.
2. Jump to the object at front-slight-left, slightly far.
3. Rotate(90)

After executing the actions, what is the ego relation of basket rel...

🤔 Assistant Answer (click to toggle)
THINK: From start, the only front-slight-right mid-distance object is the yellow door, so jump there. From the yellow door facing north, the front-slight-left slightly-far object is the plant, so jump to plant. Rotate 90° to face east. Basket is to the right/east of plant at a close separation, so i...

✅ Evaluation Results

id: 79708c6ef79fe3f2

question: You return to your starting position and face north. You will execute the following action sequence: 1. Jump to the object at front-slight-right, mid distance. 2. Jump to the object at front-slight-left, slightly far. 3. Rotate(90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-right, mid distance

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: use_model_cogmap

Question 2 (ID: 52fe3e3f1a964c59)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(-90)
2. Jump to the object at front-slight-right, mid distance.
3. Rotate(-180)
4. Jump to the object at front-left, slightly far.
5. Rotate(-90)

After executing the actions, what is the e...

🤔 Assistant Answer (click to toggle)
THINK: After the action sequence, the jumps place me at the cap’s position; the basket is 2 units straight ahead from there when I’m facing north, so it is in front at a near distance.
FINAL ANSWER:
front, near...

✅ Evaluation Results

id: 52fe3e3f1a964c59

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(-90) 2. Jump to the object at front-slight-right, mid distance. 3. Rotate(-180) 4. Jump to the object at front-left, slightly far. 5. Rotate(-90) After executing the actions, what is the ego relation of basket relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front-slight-right, slightly far

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: use_model_cogmap

Question 3 (ID: 26bdb606439e4c23)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will execute the following action sequence:
1. Rotate(90)
2. Jump to the object at front-right, mid distance.
3. Jump to the object at front-right, mid distance.

After executing the actions, what is the ego relation of chair relative to you?
...

🤔 Assistant Answer (click to toggle)
THINK: After returning to start facing north, Rotate(90) makes me face east. The object at front-right, mid distance is the brown door; jumping there keeps facing east. From the brown door facing east, the object at front-right, mid distance is the table; jumping there keeps facing east. We know cha...

✅ Evaluation Results

id: 26bdb606439e4c23

question: You return to your starting position and face north. You will execute the following action sequence: 1. Rotate(90) 2. Jump to the object at front-right, mid distance. 3. Jump to the object at front-right, mid distance. After executing the actions, what is the ego relation of chair relative to you? Answer format: <ego direction>, <distance> Example: front, near

action: None

answer: front, near

task_type: Action2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at...

🤔 Assistant Answer (click to toggle)
THINK: The final view matches what you see from the brown door after turning to face into room 1 (a 90° clockwise turn from the orientation you have after jumping there). From the start, you must first jump to the yellow door (visible), turn to face the brown door so it’s in FOV, jump to it, then ro...

✅ Evaluation Results

id: e845c6e72911adc5

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: scooter is at front-left, mid distance, facing backward; shoes is at front-slight-right, slightly far, facing left; wine is at front-right, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [7, 3]

final_ori: [-1, 0]

room_id: [1, 3]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos'], ['rotate', 180]]

final_observation: [{'name': 'scooter', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'shoes', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: True

ori_match: True

final_pos: [7.0, 3.0]

final_ori: [-1, 0]

visible_match: True

score: 1

evaluation_mode: use_model_cogmap

Question 2 (ID: 9e96f120288b1fd3)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
basket is at front-right, mid distance

What action sequence led to this final view? The action sequence must be valid and onl...

🤔 Assistant Answer (click to toggle)
THINK:
To see basket front-right at mid distance, end at the television facing north; from the yellow-door observations, television is west of cap and cap is south of basket, making basket northeast of television at a mid distance. From the start, only the yellow door is directly jumpable, so rotate...

✅ Evaluation Results

id: 9e96f120288b1fd3

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: basket is at front-right, mid distance What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [5, 14]

final_ori: [1, 0]

room_id: 2

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'yellow door'], ['jumpto', 'plant'], ['rotate', 90]]

final_observation: [{'name': 'basket', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: False

ori_match: False

final_pos: [5.0, 10.0]

final_ori: [0, 1]

visible_match: True

score: 1

evaluation_mode: use_model_cogmap

Question 3 (ID: 58129cad65341385)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
Then you have executed an action sequence and changed to a new location and facing direction.
You observe the following:
cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-lef...

🤔 Assistant Answer (click to toggle)
THINK: To see cap/basket/plant in the same configuration while not listing television, the agent likely jumped onto the television after first reaching the yellow door (television then coincides with the agent’s position and is not listed). A Rotate(0) is needed because JumpTo cannot be the first mo...

✅ Evaluation Results

id: 58129cad65341385

question: You return to your starting position and face north. Then you have executed an action sequence and changed to a new location and facing direction. You observe the following: cap is at front-right, mid distance, facing right; basket is at front-slight-right, slightly far; plant is at front-slight-left, slightly far What action sequence led to this final view? The action sequence must be valid and only contain move actions. Answer format: <sequence of move actions> Example: JumpTo(lamp), Rotate(90)

action: None

answer:

final_pos: [6, 8]

final_ori: [0, 1]

room_id: [1, 2]

init_pos: [5, 5]

init_ori: [0, 1]

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

minimal_plan: [['jumpto', 'initial_pos']]

final_observation: [{'name': 'cap', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'basket', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': None}, {'name': 'plant', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': None}]

task_type: View2ActionTextEvaluationTask

choices: []

kwargs:

(none)

pos_match: False

ori_match: True

final_pos: [5.0, 10.0]

final_ori: [0, 1]

visible_match: False

score: 0

evaluation_mode: use_model_cogmap

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: wine, chair, backpack, plant, table.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK: Use the established global cognitive map coordinates relative to the initial origin (0,0), then list requested objects in order.
FINAL ANSWER:
(-3, 2); (8, -4); (-2, -3); (0, 8); (6, -4)...

✅ Evaluation Results

id: 77fee2388e671ed1

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: wine, chair, backpack, plant, table. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[-3, 1], [6, -3], [-4, -3], [0, 9], [4, -3]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.773

threshold: 0.900

score: 0.773

evaluation_mode: use_model_cogmap

Question 2 (ID: 86e022f45899546e)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: table, television, backpack, toilet.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Use the allocentric coordinates previously mapped with the initial agent start as (0,0), x=east/right, y=north/up; extract in the requested object order.
FINAL ANSWER:
(6, -4); (0, 6); (-2, -3); (8, -1)...

✅ Evaluation Results

id: 86e022f45899546e

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: table, television, backpack, toilet. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[4, -3], [0, 5], [-4, -3], [8, -1]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.833

threshold: 0.900

score: 0.833

evaluation_mode: use_model_cogmap

Question 3 (ID: 5f8f2517c700a2b9)

❓ Evaluation Question (click to toggle)
Treat your starting position as the origin (0, 0) while facing north.
Report allocentric coordinates using (x right/east, y up/north).
Objects: toilet, scooter, chair, television, plant.
Answer format: (x0, y0); (x1, y1); ... in the same order.
Example: (1, 0); (-2, 3); (0, -1)
...

🤔 Assistant Answer (click to toggle)
THINK:
Use the previously constructed allocentric global map where the initial agent position is (0,0) and report the requested objects’ coordinates in order.
FINAL ANSWER:
(8, -1); (0, -4); (8, -4); (0, 6); (0, 8)...

✅ Evaluation Results

id: 5f8f2517c700a2b9

question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: toilet, scooter, chair, television, plant. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)

action: None

answer: [[8, -1], [0, -3], [6, -3], [0, 5], [0, 9]]

task_type: AlloMappingEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.881

threshold: 0.900

score: 0.881

evaluation_mode: use_model_cogmap

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning clockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: basket, bike, scooter, shoes, table.
List t...

🤔 Assistant Answer (click to toggle)
THINK: Compute each object’s clockwise bearing from the start (0,0) with 0°=north using arctan2(dx,dy), then sort by increasing bearing over a 0–360° clockwise sweep.
FINAL ANSWER:
basket, bike, table, scooter, shoes...

✅ Evaluation Results

id: c9f33275797c1371

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning clockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: basket, bike, scooter, shoes, table. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['basket', 'bike', 'table', 'scooter', 'shoes']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 2 (ID: 88f524a1ea9bb292)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, wine.
List them i...

🤔 Assistant Answer (click to toggle)
THINK: Compute bearings from start (0,0) with 0°=north and CCW rotation encountering decreasing (more negative) bearings: wine ≈ -56°, backpack ≈ -146°, scooter at 180° (equiv. -180°). Order: wine, then backpack, then scooter.
FINAL ANSWER:
wine, backpack, scooter...

✅ Evaluation Results

id: 88f524a1ea9bb292

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 3 (ID: fa85ac27ecb06dfa)

❓ Evaluation Question (click to toggle)
You return to your starting position and face north.
You will perform a full 360-degree rotation by continuously turning counterclockwise in place.
Assume all walls are removed (you can see through walls), so every object is visible.
Focus on this set of objects: backpack, scooter, table, wine.
List...

🤔 Assistant Answer (click to toggle)
THINK: Compute bearings from start (0,0) facing north (0°). As I rotate counterclockwise, I encounter objects in decreasing bearing order from 0° down to -180°, then continuing (wrapping) to +180° back toward 0°. Bearings: wine ≈ -56°, backpack ≈ -146°, scooter = -180°, table ≈ +124° (equiv -236°). ...

✅ Evaluation Results

id: fa85ac27ecb06dfa

question: You return to your starting position and face north. You will perform a full 360-degree rotation by continuously turning counterclockwise in place. Assume all walls are removed (you can see through walls), so every object is visible. Focus on this set of objects: backpack, scooter, table, wine. List them in the exact order they appear directly ahead while you rotate. If two objects share a bearing, place the nearer one first. Answer format: <object_name1>, <object_name2>, ... Example: mug, sofa, plant

action: None

answer: ['wine', 'backpack', 'scooter', 'table']

task_type: RotEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (1, -3) and face north.
What is the egocentric relation of wine?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK: From (1,-3) to wine (-3,2) is 4 left and 5 forward: angle ≈ -38.7° (front-left). Distance ≈ 6.4 → slightly far.
FINAL ANSWER:
front-left, slightly far...

✅ Evaluation Results

id: efa7a1eae6c023bd

question: Still treat your initial position as origin (0, 0) You move to (1, -3) and face north. What is the egocentric relation of wine? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-left, slightly far

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 1

evaluation_mode: use_model_cogmap

Question 2 (ID: 29dc2089738c91f3)

❓ Evaluation Question (click to toggle)
Treat the brown door as the new 'origin' (0, 0).
You move to (5, -2) and face west.
What is the egocentric relation of chair?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK: Brown door is (0,0). Chair is at (5,-2). Agent is at (5,-2) facing west, so chair and agent coincide: distance 0, direction can be treated as front.
FINAL ANSWER:
front, same distance...

✅ Evaluation Results

id: 29dc2089738c91f3

question: Treat the brown door as the new 'origin' (0, 0). You move to (5, -2) and face west. What is the egocentric relation of chair? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-right, near

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: use_model_cogmap

Question 3 (ID: 0f994784bf1c8d5b)

❓ Evaluation Question (click to toggle)
Still treat your initial position as origin (0, 0)
You move to (-1, 0) and face west.
What is the egocentric relation of shoes?

Answer format: <direction>, <distance>
Example: front, near
...

🤔 Assistant Answer (click to toggle)
THINK:
From agent at (-1,0) facing west, shoes at (-2,-1) are 1 unit forward and 1 unit left; distance √2 ≈ 1.41 (near), bearing -45° (front-left bin).
FINAL ANSWER:
front-left, near...

✅ Evaluation Results

id: 0f994784bf1c8d5b

question: Still treat your initial position as origin (0, 0) You move to (-1, 0) and face west. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near

action: None

answer: front-slight-left, mid distance

task_type: Location2ViewEvaluationTask

choices: []

kwargs:

(none)

score: 0

evaluation_mode: use_model_cogmap

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

❓ Evaluation Question (click to toggle)
You move to a new location and face north.
You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answer forma...

🤔 Assistant Answer (click to toggle)
THINK: With agent facing north, “yellow door at front (slightly far)” implies the agent shares the same x as the yellow door and is 4–8 units south of it. “brown door at front-right (near)” implies the agent is 1 unit west and 1 unit south of the brown door. The consistent integer location satisfyin...

✅ Evaluation Results

id: 3943df1f7c7f8b07

question: You move to a new location and face north. You observe: wine is at front-left, slightly far; brown door is at front-right, near, on right wall; yellow door is at front, slightly far, on front wall Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [1, -3]

final_pos: [6, 2]

final_ori: [0, 1]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'wine', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': None}, {'name': 'brown door', 'direction': 'front-right', 'distance': 'near', 'orientation': 'on right wall'}, {'name': 'yellow door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.639

raw_score: 0.639

score: 0.639

evaluation_mode: use_model_cogmap

Question 2 (ID: f08df2fab1aea39f)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall
Treat the brown door as the new 'origin' (0, 0).
What is your new 2D coordinate (x, y)?

A...

🤔 Assistant Answer (click to toggle)
THINK: Facing west means “front” is toward negative x. Brown door is front-slight-right, so it is west and slightly north of me; therefore I am east and slightly south of the door. Use a plausible slightly-far displacement of 6 west and 2 north from me to the door (angle ~18° fits slight-right), so ...

✅ Evaluation Results

id: f08df2fab1aea39f

question: You move to a new location and face west. You observe: chair is at front-right, near, facing left; table is at front-slight-right, mid distance; brown door is at front-slight-right, slightly far, on front wall Treat the brown door as the new 'origin' (0, 0). What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [5, -2]

final_pos: [12, 1]

final_ori: [-1, 0]

room_id: 3

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'chair', 'direction': 'front-right', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'table', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': None}, {'name': 'brown door', 'direction': 'front-slight-right', 'distance': 'slightly far', 'orientation': 'on front wall'}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.831

raw_score: 0.831

score: 0.831

evaluation_mode: use_model_cogmap

Question 3 (ID: ce196c535efde5f3)

❓ Evaluation Question (click to toggle)
You move to a new location and face west.
You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance
Still treat your initial position as origin (0, 0)
What is your new 2D coordinate (x, y)?

Answe...

🤔 Assistant Answer (click to toggle)
THINK: Using the previously built global map coordinates for shoes, backpack, and wine, solve for the integer agent position that best matches the observed egocentric bearings/distances while facing west; the consistent fit is at (1, 0).
FINAL ANSWER:
(1, 0)...

✅ Evaluation Results

id: ce196c535efde5f3

question: You move to a new location and face west. You observe: shoes is at front-slight-left, mid distance, facing left; backpack is at front-left, slightly far, facing left; wine is at front-right, mid distance Still treat your initial position as origin (0, 0) What is your new 2D coordinate (x, y)? Answer format: (x, y) Example: (2, -1)

action: None

answer:

coord: [-1, 0]

final_pos: [4, 5]

final_ori: [-1, 0]

room_id: 1

object_positions:

scooter: [5, 2]

television: [5, 10]

chair: [11, 2]

shoes: [1, 4]

cap: [7, 10]

toilet: [13, 4]

backpack: [1, 2]

wine: [2, 6]

basket: [7, 12]

table: [9, 2]

plant: [5, 14]

bike: [11, 6]

brown door: [7, 3]

yellow door: [6, 8]

object_orientations:

scooter: [1, 0]

television: [0, 1]

chair: [0, -1]

shoes: [0, -1]

cap: [1, 0]

toilet: [1, 0]

backpack: [0, -1]

bike: [1, 0]

brown door: [1, 0]

yellow door: [0, 1]

final_observation: [{'name': 'shoes', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing left'}, {'name': 'backpack', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'wine', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': None}]

gate_info:

brown door:

room_ids: [1, 3]

ori_by_room:

1: [-1, 0]

3: [1, 0]

yellow door:

room_ids: [1, 2]

ori_by_room:

1: [0, -1]

2: [0, 1]

object_rooms:

scooter: 1

television: 2

chair: 3

shoes: 1

cap: 2

toilet: 3

backpack: 1

wine: 1

basket: 2

table: 3

plant: 2

bike: 3

brown door: [1, 3]

yellow door: [1, 2]

task_type: View2LocationTextEvaluationTask

choices: []

kwargs:

(none)

similarity: 0.135

raw_score: 0.135

score: 0.135

evaluation_mode: use_model_cogmap

Model: gpt-5.2

sample_run09

Select Configuration:

📊 Sample Metrics

🔍 Exploration

✅ Evaluation

✅ Evaluation (prompt_cogmap)

✅ Evaluation (use_gt_cogmap)

✅ Evaluation (use_model_cogmap)

🧠 Cognitive Map

🧭 False Belief CogMap

📊 Performance Charts

Cognitive Map (Update)

Cognitive Map (Full)

Cognitive Map (Self-Tracking)

FB CogMap (Unchanged)

Fog Probe F1

Fog Probe Precision

Fog Probe Recall

Position Update

Facing Update

Position Stability

Facing Stability

🌍 Exploration Phase

🔄 Turn 1

🔄 Turn 2

🔄 Turn 3

🔄 Turn 4

🔄 Turn 5

🔄 Turn 6

🔄 Turn 7

🔄 Turn 8

🔄 Turn 9

🧭 False Belief Exploration

🔄 FB Turn 10

🔄 FB Turn 11

🔄 FB Turn 12

🔄 FB Turn 13

🔄 FB Turn 14

🔄 FB Turn 15

🔄 FB Turn 16

🔄 FB Turn 17

🔄 FB Turn 18

🔄 FB Turn 19

📊 Evaluation (default)

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

Question 2 (ID: f7b63fa7e2d19d32)

Question 3 (ID: 093963cbd99a1c04)

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

Question 2 (ID: c74b1f5f919fdbbc)

Question 3 (ID: 20fcddf7da613597)

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

Question 2 (ID: b042fd780599b324)

Question 3 (ID: b331cdf635e89588)

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

Question 2 (ID: 52fe3e3f1a964c59)

Question 3 (ID: 26bdb606439e4c23)

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

Question 2 (ID: 9e96f120288b1fd3)

Question 3 (ID: 58129cad65341385)

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

Question 2 (ID: 86e022f45899546e)

Question 3 (ID: 5f8f2517c700a2b9)

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

Question 2 (ID: 88f524a1ea9bb292)

Question 3 (ID: fa85ac27ecb06dfa)

📊 Task: RotDualEvaluationTask

Question 1 (ID: b72c000118d6dabd)

Question 2 (ID: 08504c64e20ddfdb)

Question 3 (ID: 36155bdbf69a1da7)

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

Question 2 (ID: 29dc2089738c91f3)