Model: gpt-5.2

sample_run09

Select Configuration:

📊 Sample Metrics

🔍 Exploration

last_node_coverage: 1
last_edge_coverage: 0.439
n_exploration_steps: 9
action_counts:
move: 2
rotate: 5
return: 0
observe: 8
term: 1
forced_term: 0
query: 0
action_cost: 8
final_information_gain: 0.826
action_fail_ratio: 0
valid_action_ratio: 1
false_belief_steps: 10
false_belief_f1: 1
false_belief_f1_position: 1
false_belief_f1_facing: 1
false_belief_action_cost: 9
false_belief_action_cost_after_seen: 0

✅ Evaluation

overall:
n_total: 27
total_score: 20.103
avg_accuracy: 0.745
per_task:
DirectionEvaluationTask:
n_total: 3
task_score: 2.500
avg_accuracy: 0.833
PovEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
BackwardPovTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Action2ViewEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
View2ActionTextEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
AlloMappingEvaluationTask:
n_total: 3
task_score: 2.501
avg_accuracy: 0.834
RotEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Location2ViewEvaluationTask:
n_total: 3
task_score: 1.500
avg_accuracy: 0.500
View2LocationTextEvaluationTask:
n_total: 3
task_score: 1.602
avg_accuracy: 0.534

✅ Evaluation (prompt_cogmap)

overall:
n_total: 27
total_score: 20.382
avg_accuracy: 0.755
per_task:
DirectionEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
PovEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
BackwardPovTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Action2ViewEvaluationTask:
n_total: 3
task_score: 1.500
avg_accuracy: 0.500
View2ActionTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
AlloMappingEvaluationTask:
n_total: 3
task_score: 1.777
avg_accuracy: 0.592
RotEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Location2ViewEvaluationTask:
n_total: 3
task_score: 1.500
avg_accuracy: 0.500
View2LocationTextEvaluationTask:
n_total: 3
task_score: 1.605
avg_accuracy: 0.535

✅ Evaluation (use_gt_cogmap)

overall:
n_total: 27
total_score: 26
avg_accuracy: 0.963
per_task:
DirectionEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
PovEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
BackwardPovTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Action2ViewEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
View2ActionTextEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
AlloMappingEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
RotEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Location2ViewEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
View2LocationTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1

✅ Evaluation (use_model_cogmap)

overall:
n_total: 27
total_score: 19.592
avg_accuracy: 0.726
per_task:
DirectionEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
PovEvaluationTask:
n_total: 3
task_score: 2.500
avg_accuracy: 0.833
BackwardPovTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Action2ViewEvaluationTask:
n_total: 3
task_score: 1
avg_accuracy: 0.333
View2ActionTextEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
AlloMappingEvaluationTask:
n_total: 3
task_score: 2.486
avg_accuracy: 0.829
RotEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Location2ViewEvaluationTask:
n_total: 3
task_score: 1
avg_accuracy: 0.333
View2LocationTextEvaluationTask:
n_total: 3
task_score: 1.605
avg_accuracy: 0.535

🧠 Cognitive Map

exploration:
error:
local_vs_gt_local_avg:
dir: 0.744
facing: 1
pos: 0.812
overall: 0.852
global_vs_gt_global_avg:
dir: 0.808
facing: 0.981
pos: 0.839
overall: 0.876
agent_vs_gt_agent_avg:
dir: 0.778
facing: 1
pos: 0.924
overall: 0.901
newly_observed_vs_gt_local_avg:
dir: 0.733
facing: 1
pos: 0.809
overall: 0.848
correctness:
last_global_vs_gt_full:
dir: 0.858
facing: 1
pos: 0.797
overall: 0.885
consistency:
local_vs_global_avg:
dir: 0.706
facing: 1
pos: 0.800
overall: 0.835
position_update_avg: 0.720
facing_update_avg: 0.971
position_stability_avg: 0.720
facing_stability_avg: 0.971
fog_probe:
f1_avg: 0.524
precision_avg: 0.429
recall_avg: 0.714
cogmap_fb:
metrics:
changed:
dir: None
pos: 0.801
facing: 1
overall: None
retention:
dir: None
pos: 0.264
facing: 0
overall: None
unchanged:
dir: 0.480
facing: 0.741
pos: 0.555
overall: 0.592
inertia: 0.001
inertia_list: [0.0012011510177694707]
unchanged_retention:
dir: None
pos: 0.808
facing: 1
overall: None
unchanged_retention_minus_retention:
pos: 0.894
facing: 1
unchanged_exploration:
dir: 0.891
facing: 1
pos: 0.813
overall: 0.901

🧭 False Belief CogMap

inertia: 0.001
changed:
dir: None
pos: 0.801
facing: 1
overall: None
retention:
dir: None
pos: 0.264
facing: 0
overall: None
unchanged:
dir: 0.480
facing: 0.741
pos: 0.555
overall: 0.592
unchanged_retention:
dir: None
pos: 0.808
facing: 1
overall: None
unchanged_retention_minus_retention:
pos: 0.894
facing: 1
unchanged_exploration:
dir: 0.891
facing: 1
pos: 0.813
overall: 0.901

📊 Performance Charts

Cognitive Map (Update)
Global Update Metrics
Cognitive Map (Full)
Global Full Metrics
Cognitive Map (Self-Tracking)
Global Self-Tracking Metrics
FB CogMap (Unchanged)
False Belief CogMap Unchanged per Turn
Fog Probe F1
Fog Probe F1 per Turn
Fog Probe Precision
Fog Probe Precision per Turn
Fog Probe Recall
Fog Probe Recall per Turn
Position Update
Position Update per Turn
Facing Update
Facing Update per Turn
Position Stability
Position Stability per Turn
Facing Stability
Facing Stability per Turn

🌍 Exploration Phase

🔄 Turn 1

💬 Assistant Action
Actions: [Observe()]
📊 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"
  }
}
📊 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"
  }
}
🗺️ 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
Current state
State at Turn 1

🔄 Turn 2

💬 Assistant Action
Actions: [JumpTo(yellow door), Observe()]
📊 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"
  }
}
📊 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"
  }
}
🗺️ 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
Previous state
State before Turn 2
Current state
State at Turn 2

🔄 Turn 3

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📊 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"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {}
}
🎯 Ground Truth
(no data)
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {}
}
🎯 Ground Truth
(no data)
🗺️ 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
Previous state
State before Turn 3
Current state
State at Turn 3

🔄 Turn 4

💬 Assistant Action
Actions: [Rotate(180), Observe()]
📊 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"
  }
}
📊 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"
  }
}
🗺️ 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
Previous state
State before Turn 4
Current state
State at Turn 4

🔄 Turn 5

💬 Assistant Action
Actions: [Rotate(-90), Observe()]
📊 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"
  }
}
📊 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
Previous state
State before Turn 5
Current state
State at Turn 5

🔄 Turn 6

💬 Assistant Action
Actions: [JumpTo(brown door), Observe()]
📊 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"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {}
}
🎯 Ground Truth
(no data)
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {}
}
🎯 Ground Truth
(no data)
🗺️ 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
Previous state
State before Turn 6
Current state
State at Turn 6

🔄 Turn 7

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📊 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"
  }
}
📊 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)
🗺️ 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
Previous state
State before Turn 7
Current state
State at Turn 7

🔄 Turn 8

💬 Assistant Action
Actions: [Rotate(180), Observe()]
📊 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"
  }
}
📊 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"
  }
}
🗺️ 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
Previous state
State before Turn 8
Current state
State at Turn 8

🔄 Turn 9

💬 Assistant Action
Actions: [Term()]
📊 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
Previous state
State before Turn 9
Current state
State at Turn 9

🧭 False Belief Exploration

🔄 FB Turn 10

💬 Assistant Action
Actions: [Observe()]
📈 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']
Current state
State at Turn 1

🔄 FB Turn 11

💬 Assistant Action
Actions: [JumpTo(yellow door), Observe()]
📈 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']
Previous state
State before Turn 2
Current state
State at Turn 2

🔄 FB Turn 12

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📈 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: []
Previous state
State before Turn 3
Current state
State at Turn 3

🔄 FB Turn 13

💬 Assistant Action
Actions: [Rotate(180), Observe()]
📈 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']
Previous state
State before Turn 4
Current state
State at Turn 4

🔄 FB Turn 14

💬 Assistant Action
Actions: [Rotate(-90), Observe()]
📈 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']
Previous state
State before Turn 5
Current state
State at Turn 5

🔄 FB Turn 15

💬 Assistant Action
Actions: [Rotate(180), Observe()]
📈 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: []
Previous state
State before Turn 6
Current state
State at Turn 6

🔄 FB Turn 16

💬 Assistant Action
Actions: [Rotate(180), JumpTo(brown door), Observe()]
📈 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: []
Previous state
State before Turn 7
Current state
State at Turn 7

🔄 FB Turn 17

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📈 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: []
Previous state
State before Turn 8
Current state
State at Turn 8

🔄 FB Turn 18

💬 Assistant Action
Actions: [Rotate(180), Observe()]
📈 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']
Previous state
State before Turn 9
Current state
State at Turn 9

🔄 FB Turn 19

💬 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: []
Previous state
State before Turn 10
Current state
State at Turn 10

📊 Evaluation (default)

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

✅ 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 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
Evaluation state
Q2: DirectionEvaluationTask

Question 3 (ID: 093963cbd99a1c04)

✅ 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
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

✅ 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
Evaluation state
Q1: PovEvaluationTask

Question 2 (ID: c74b1f5f919fdbbc)

✅ 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
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 20fcddf7da613597)

✅ 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
Evaluation state
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

✅ 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
Evaluation state
Q1: BackwardPovTextEvaluationTask

Question 2 (ID: b042fd780599b324)

✅ 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
Evaluation state
Q2: BackwardPovTextEvaluationTask

Question 3 (ID: b331cdf635e89588)

✅ 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
Evaluation state
Q3: BackwardPovTextEvaluationTask

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

✅ 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
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: 52fe3e3f1a964c59)

✅ 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
Evaluation state
Q2: Action2ViewEvaluationTask

Question 3 (ID: 26bdb606439e4c23)

✅ 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
Evaluation state
Q3: Action2ViewEvaluationTask

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

✅ 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
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: 9e96f120288b1fd3)

✅ 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
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 58129cad65341385)

✅ 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
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

✅ 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
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: 86e022f45899546e)

✅ 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
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 5f8f2517c700a2b9)

✅ 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
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

✅ 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
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 88f524a1ea9bb292)

✅ 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
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: fa85ac27ecb06dfa)

✅ 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
Evaluation state
Q3: RotEvaluationTask

📊 Task: RotDualEvaluationTask

Question 1 (ID: b72c000118d6dabd)

✅ 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
Evaluation state
Q1: RotDualEvaluationTask

Question 2 (ID: 08504c64e20ddfdb)

✅ 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
Evaluation state
Q2: RotDualEvaluationTask

Question 3 (ID: 36155bdbf69a1da7)

✅ 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
Evaluation state
Q3: RotDualEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

✅ 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
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 29dc2089738c91f3)

✅ 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
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 0f994784bf1c8d5b)

✅ 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
Evaluation state
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

✅ 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
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: f08df2fab1aea39f)

✅ 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
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: ce196c535efde5f3)

✅ 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
Evaluation state
Q3: View2LocationTextEvaluationTask

📊 Evaluation (prompt_cogmap)

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

✅ 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
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: f7b63fa7e2d19d32)

✅ 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
Evaluation state
Q2: DirectionEvaluationTask

Question 3 (ID: 093963cbd99a1c04)

✅ 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
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

✅ 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
Evaluation state
Q1: PovEvaluationTask

Question 2 (ID: c74b1f5f919fdbbc)

✅ 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
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 20fcddf7da613597)

✅ 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
Evaluation state
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

✅ 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
Evaluation state
Q1: BackwardPovTextEvaluationTask

Question 2 (ID: b042fd780599b324)

✅ 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
Evaluation state
Q2: BackwardPovTextEvaluationTask

Question 3 (ID: b331cdf635e89588)

✅ 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
Evaluation state
Q3: BackwardPovTextEvaluationTask

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

✅ 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
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: 52fe3e3f1a964c59)

✅ 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
Evaluation state
Q2: Action2ViewEvaluationTask

Question 3 (ID: 26bdb606439e4c23)

✅ 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
Evaluation state
Q3: Action2ViewEvaluationTask

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

✅ 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
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: 9e96f120288b1fd3)

✅ 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
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 58129cad65341385)

✅ 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
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

✅ 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
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: 86e022f45899546e)

✅ 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
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 5f8f2517c700a2b9)

✅ 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
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

✅ 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
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 88f524a1ea9bb292)

✅ 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
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: fa85ac27ecb06dfa)

✅ 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
Evaluation state
Q3: RotEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

✅ 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
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 29dc2089738c91f3)

✅ 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
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 0f994784bf1c8d5b)

✅ 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
Evaluation state
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

✅ 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
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: f08df2fab1aea39f)

✅ 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
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: ce196c535efde5f3)

✅ 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
Evaluation state
Q3: View2LocationTextEvaluationTask

📊 Evaluation (use_gt_cogmap)

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

✅ 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
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: f7b63fa7e2d19d32)

✅ 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
Evaluation state
Q2: DirectionEvaluationTask

Question 3 (ID: 093963cbd99a1c04)

✅ 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
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

✅ 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
Evaluation state
Q1: PovEvaluationTask

Question 2 (ID: c74b1f5f919fdbbc)

✅ 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
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 20fcddf7da613597)

✅ 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
Evaluation state
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

✅ 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
Evaluation state
Q1: BackwardPovTextEvaluationTask

Question 2 (ID: b042fd780599b324)

✅ 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
Evaluation state
Q2: BackwardPovTextEvaluationTask

Question 3 (ID: b331cdf635e89588)

✅ 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
Evaluation state
Q3: BackwardPovTextEvaluationTask

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

✅ 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
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: 52fe3e3f1a964c59)

✅ 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
Evaluation state
Q2: Action2ViewEvaluationTask

Question 3 (ID: 26bdb606439e4c23)

✅ 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
Evaluation state
Q3: Action2ViewEvaluationTask

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

✅ 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
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: 9e96f120288b1fd3)

✅ 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
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 58129cad65341385)

✅ 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
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

✅ 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
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: 86e022f45899546e)

✅ 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
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 5f8f2517c700a2b9)

✅ 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
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

✅ 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
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 88f524a1ea9bb292)

✅ 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
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: fa85ac27ecb06dfa)

✅ 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
Evaluation state
Q3: RotEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

✅ 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
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 29dc2089738c91f3)

✅ 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
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 0f994784bf1c8d5b)

✅ 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
Evaluation state
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

✅ 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
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: f08df2fab1aea39f)

✅ 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
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: ce196c535efde5f3)

✅ 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
Evaluation state
Q3: View2LocationTextEvaluationTask

📊 Evaluation (use_model_cogmap)

📊 Task: DirectionEvaluationTask

Question 1 (ID: 2a3ea1ab8ec1bd26)

✅ 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
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: f7b63fa7e2d19d32)

✅ 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
Evaluation state
Q2: DirectionEvaluationTask

Question 3 (ID: 093963cbd99a1c04)

✅ 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
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: 3976e12c4008e19b)

✅ 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
Evaluation state
Q1: PovEvaluationTask

Question 2 (ID: c74b1f5f919fdbbc)

✅ 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
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 20fcddf7da613597)

✅ 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
Evaluation state
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: 221e1938c962c6af)

✅ 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
Evaluation state
Q1: BackwardPovTextEvaluationTask

Question 2 (ID: b042fd780599b324)

✅ 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
Evaluation state
Q2: BackwardPovTextEvaluationTask

Question 3 (ID: b331cdf635e89588)

✅ 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
Evaluation state
Q3: BackwardPovTextEvaluationTask

📊 Task: Action2ViewEvaluationTask

Question 1 (ID: 79708c6ef79fe3f2)

✅ 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
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: 52fe3e3f1a964c59)

✅ 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
Evaluation state
Q2: Action2ViewEvaluationTask

Question 3 (ID: 26bdb606439e4c23)

✅ 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
Evaluation state
Q3: Action2ViewEvaluationTask

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: e845c6e72911adc5)

✅ 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
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: 9e96f120288b1fd3)

✅ 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
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 58129cad65341385)

✅ 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
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: 77fee2388e671ed1)

✅ 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
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: 86e022f45899546e)

✅ 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
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 5f8f2517c700a2b9)

✅ 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
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: c9f33275797c1371)

✅ 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
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 88f524a1ea9bb292)

✅ 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
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: fa85ac27ecb06dfa)

✅ 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
Evaluation state
Q3: RotEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: efa7a1eae6c023bd)

✅ 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
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 29dc2089738c91f3)

✅ 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
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 0f994784bf1c8d5b)

✅ 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
Evaluation state
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 3943df1f7c7f8b07)

✅ 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
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: f08df2fab1aea39f)

✅ 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
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: ce196c535efde5f3)

✅ 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
Evaluation state
Q3: View2LocationTextEvaluationTask