Model: gpt-5.2

sample_run05

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: 0.874
action_fail_ratio: 0
valid_action_ratio: 1
false_belief_steps: 5
false_belief_f1: 1
false_belief_f1_position: 1
false_belief_f1_facing: 1
false_belief_action_cost: 4
false_belief_action_cost_after_seen: 0

✅ Evaluation

overall:
n_total: 27
total_score: 19.505
avg_accuracy: 0.722
per_task:
DirectionEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
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: 2.500
avg_accuracy: 0.833
View2ActionTextEvaluationTask:
n_total: 3
task_score: 0
avg_accuracy: 0
AlloMappingEvaluationTask:
n_total: 3
task_score: 2.705
avg_accuracy: 0.902
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: 2.800
avg_accuracy: 0.933

✅ Evaluation (prompt_cogmap)

overall:
n_total: 27
total_score: 22.784
avg_accuracy: 0.844
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: 2.500
avg_accuracy: 0.833
View2ActionTextEvaluationTask:
n_total: 3
task_score: 1
avg_accuracy: 0.333
AlloMappingEvaluationTask:
n_total: 3
task_score: 2.485
avg_accuracy: 0.828
RotEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Location2ViewEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
View2LocationTextEvaluationTask:
n_total: 3
task_score: 2.800
avg_accuracy: 0.933

✅ Evaluation (use_gt_cogmap)

overall:
n_total: 27
total_score: 25.800
avg_accuracy: 0.956
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: 2.800
avg_accuracy: 0.933

✅ Evaluation (use_model_cogmap)

overall:
n_total: 27
total_score: 24.353
avg_accuracy: 0.902
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: 2
avg_accuracy: 0.667
View2ActionTextEvaluationTask:
n_total: 3
task_score: 2
avg_accuracy: 0.667
AlloMappingEvaluationTask:
n_total: 3
task_score: 2.853
avg_accuracy: 0.951
RotEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1
Location2ViewEvaluationTask:
n_total: 3
task_score: 2.500
avg_accuracy: 0.833
View2LocationTextEvaluationTask:
n_total: 3
task_score: 3
avg_accuracy: 1

🧠 Cognitive Map

exploration:
error:
local_vs_gt_local_avg:
dir: 0.873
facing: 1
pos: 0.926
overall: 0.933
global_vs_gt_global_avg:
dir: 0.869
facing: 0.802
pos: 0.896
overall: 0.856
agent_vs_gt_agent_avg:
dir: 1
facing: 1
pos: 0.948
overall: 0.983
newly_observed_vs_gt_local_avg:
dir: 0.867
facing: 1
pos: 0.928
overall: 0.932
correctness:
last_global_vs_gt_full:
dir: 0.958
facing: 1
pos: 0.899
overall: 0.953
consistency:
local_vs_global_avg:
dir: 0.860
facing: 0.600
pos: 0.901
overall: 0.787
position_update_avg: 0.757
facing_update_avg: 0.857
position_stability_avg: 0.757
facing_stability_avg: 0.857
fog_probe:
f1_avg: 0.668
precision_avg: 0.589
recall_avg: 0.867
cogmap_fb:
metrics:
changed:
dir: None
pos: 0.769
facing: 1
overall: None
retention:
dir: None
pos: 0.334
facing: 0
overall: None
unchanged:
dir: 0.860
facing: 1
pos: 0.837
overall: 0.899
inertia: 0.000
inertia_list: [2.0202454451498282e-07, 5.693020785804219e-12]
unchanged_retention:
dir: None
pos: 0.837
facing: 1
overall: None
unchanged_retention_minus_retention:
pos: 0.841
facing: 1
unchanged_exploration:
dir: 0.982
facing: 1
pos: 0.916
overall: 0.966

🧭 False Belief CogMap

inertia: 0.000
changed:
dir: None
pos: 0.769
facing: 1
overall: None
retention:
dir: None
pos: 0.334
facing: 0
overall: None
unchanged:
dir: 0.860
facing: 1
pos: 0.837
overall: 0.899
unchanged_retention:
dir: None
pos: 0.837
facing: 1
overall: None
unchanged_retention_minus_retention:
pos: 0.841
facing: 1
unchanged_exploration:
dir: 0.982
facing: 1
pos: 0.916
overall: 0.966

📊 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"
  }
}
🎯 Ground Truth (Observed)
{
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "north"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "north"
  }
}
📊 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
################
#########......#
#########......#
##DBC...#......#
##.....E#......#
##*.....#......#
##.....F+......#
##......########
##.A....########
######+#########
#......#########
#......#########
#......#########
#......#########
#......#########
#......#########
################
🔍 Fog Probe JSONs
📍 Candidates: A, B, C, D, E, F
🤖 Predicted: A, F
🎯 Ground Truth: E, F, A
🧠 Cognitive Map Metrics
Global:
dir: 1
facing: 1
pos: 1
overall: 1
Global (Full):
dir: 0.008
facing: 0.083
pos: 0.067
overall: 0.053
Local:
(none)
Local (Newly):
(none)
Fog Probe:
precision: 1
recall: 0.667
overall: 0.800
📈 Turn Metrics
node_coverage: 0
edge_coverage: 0
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
reward: -0.100
is_done: False
is_valid_action: True
Current state
State at Turn 1

🔄 Turn 2

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📊 Cognitive Map JSONs
🤖 Predicted
{
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "east"
  },
  "shoes": {
    "position": [
      5,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      3,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      3,
      1
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      7,
      -1
    ]
  },
  "blue door": {
    "position": [
      6,
      -4
    ]
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "east"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      0,
      0
    ],
    "facing": "east"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "shoes": {
      "position": [
        2,
        4
      ],
      "facing": "-y"
    },
    "rubberduck": {
      "position": [
        1,
        3
      ],
      "facing": "-x"
    },
    "alarmclock": {
      "position": [
        -1,
        3
      ],
      "facing": "-y"
    },
    "yellow door": {
      "position": [
        2,
        5
      ]
    },
    "blue door": {
      "position": [
        6,
        4
      ]
    }
  }
}
🎯 Ground Truth
{
  "alarmclock": {
    "position": [
      -1,
      2
    ],
    "facing": "west"
  },
  "shoes": {
    "position": [
      1,
      4
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      1,
      2
    ],
    "facing": "north"
  },
  "blue door": {
    "position": [
      4,
      4
    ],
    "facing": "north"
  },
  "yellow door": {
    "position": [
      1,
      6
    ],
    "facing": "east"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "shoes": {
      "position": [
        2,
        4
      ],
      "facing": "-y"
    },
    "rubberduck": {
      "position": [
        1,
        3
      ],
      "facing": "-x"
    },
    "alarmclock": {
      "position": [
        -1,
        3
      ],
      "facing": "-y"
    },
    "yellow door": {
      "position": [
        2,
        5
      ]
    },
    "blue door": {
      "position": [
        6,
        4
      ]
    }
  }
}
🎯 Ground Truth
{
  "alarmclock": {
    "position": [
      -1,
      2
    ],
    "facing": "west"
  },
  "shoes": {
    "position": [
      1,
      4
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      1,
      2
    ],
    "facing": "north"
  },
  "blue door": {
    "position": [
      4,
      4
    ],
    "facing": "north"
  },
  "yellow door": {
    "position": [
      1,
      6
    ],
    "facing": "east"
  }
}
🗺️ Symbolic Fog Map
################
#########......#
#########......#
##....C.#......#
##.....D#......#
##*.....#......#
##FA....+......#
##.E....########
##B.....########
######+#########
#......#########
#......#########
#......#########
#......#########
#......#########
#......#########
################
🔍 Fog Probe JSONs
📍 Candidates: A, B, C, D, E, F
🤖 Predicted: A, B, C, D, E, F
🎯 Ground Truth: E, F, B
🧠 Cognitive Map Metrics
Global:
dir: 0.714
facing: 1
pos: 0.867
overall: 0.860
Global (Full):
dir: 0.125
facing: 0.333
pos: 0.347
overall: 0.268
Local:
dir: 0.467
facing: 1
pos: 0.847
overall: 0.771
Local (Newly):
dir: 0.467
facing: 1
pos: 0.847
overall: 0.771
Fog Probe:
precision: 0.500
recall: 1
overall: 0.667
📈 Turn Metrics
node_coverage: 0.357
edge_coverage: 0.122
is_action_fail: False
step: 2
action_counts:
move: 0
rotate: 1
return: 0
observe: 2
term: 0
forced_term: 0
query: 0
information_gain: 0.318
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: [JumpTo(blue door), Observe()]
📊 Cognitive Map JSONs
🤖 Predicted
{
  "agent": {
    "position": [
      5,
      -4
    ],
    "facing": "east"
  },
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ]
  },
  "blue door": {
    "position": [
      5,
      -4
    ]
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "east"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "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
################
#########......#
#########......#
##..D...#......#
##..A...#......#
##......#......#
##C.....+......#
##.F....########
##B..E..########
######*#########
#......#########
#......#########
#......#########
#......#########
#......#########
#......#########
################
🔍 Fog Probe JSONs
📍 Candidates: A, B, C, D, E, F
🤖 Predicted: A, B, C, D, E, F
🎯 Ground Truth: C, F, B
🧠 Cognitive Map Metrics
Global:
dir: 0.810
facing: 1
pos: 0.931
overall: 0.913
Global (Full):
dir: 0.142
facing: 0.333
pos: 0.372
overall: 0.282
Local:
(none)
Local (Newly):
(none)
Fog Probe:
precision: 0.500
recall: 1
overall: 0.667
📈 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: 0.318
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(90), Observe()]
📊 Cognitive Map JSONs
🤖 Predicted
{
  "agent": {
    "position": [
      5,
      -4
    ],
    "facing": "south"
  },
  "shoes": {
    "position": [
      5,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      3,
      -2
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      3,
      2
    ],
    "facing": "west"
  },
  "yellow door": {
    "position": [
      4,
      -1
    ]
  },
  "blue door": {
    "position": [
      5,
      -4
    ]
  },
  "shoppingcart": {
    "position": [
      5,
      -9
    ],
    "facing": "south"
  },
  "red chair": {
    "position": [
      3,
      -7
    ],
    "facing": "south"
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "south"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "south"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "shoppingcart": {
      "position": [
        0,
        5
      ],
      "facing": "+y"
    },
    "red chair": {
      "position": [
        2,
        3
      ],
      "facing": "+y"
    }
  }
}
🎯 Ground Truth
{
  "shoppingcart": {
    "position": [
      0,
      5
    ],
    "facing": "south"
  },
  "red chair": {
    "position": [
      2,
      3
    ],
    "facing": "south"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "shoppingcart": {
      "position": [
        0,
        5
      ],
      "facing": "+y"
    },
    "red chair": {
      "position": [
        2,
        3
      ],
      "facing": "+y"
    }
  }
}
🎯 Ground Truth
{
  "shoppingcart": {
    "position": [
      0,
      5
    ],
    "facing": "south"
  },
  "red chair": {
    "position": [
      2,
      3
    ],
    "facing": "south"
  }
}
🗺️ Symbolic Fog Map
################
#########......#
#########......#
##.CK...#......#
##......#......#
##......#......#
##J..B..+......#
##......########
##AF....########
######*#########
#.EDH..#########
#....I.#########
#......#########
#......#########
#..L..G#########
#......#########
################
🔍 Fog Probe JSONs
📍 Candidates: A, B, C, D, E, F, G, H, I, J, K, L
🤖 Predicted: A, C, D, E, F, G, H, I, J, K, L
🎯 Ground Truth: F, A, J, H, E, D
🧠 Cognitive Map Metrics
Global:
dir: 0.778
facing: 1
pos: 0.854
overall: 0.877
Global (Full):
dir: 0.233
facing: 0.500
pos: 0.455
overall: 0.396
Local:
dir: 1
facing: 1
pos: 1
overall: 1
Local (Newly):
dir: 1
facing: 1
pos: 1
overall: 1
Fog Probe:
precision: 0.545
recall: 1
overall: 0.706
📈 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: 0.383
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": [
      4,
      -3
    ],
    "facing": "west"
  },
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "south"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      5,
      -1
    ]
  },
  "blue door": {
    "position": [
      4,
      -3
    ]
  },
  "shoppingcart": {
    "position": [
      4,
      -8
    ],
    "facing": "north"
  },
  "red chair": {
    "position": [
      2,
      -6
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      1,
      -5
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      -1,
      -2
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -7
    ],
    "facing": "west"
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "west"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "west"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "bike": {
      "position": [
        -2,
        3
      ],
      "facing": "-y"
    },
    "pan": {
      "position": [
        1,
        5
      ],
      "facing": "+y"
    },
    "desklamp": {
      "position": [
        -3,
        5
      ],
      "facing": "-x"
    }
  }
}
🎯 Ground Truth
{
  "bike": {
    "position": [
      -1,
      2
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      1,
      4
    ],
    "facing": "west"
  },
  "desklamp": {
    "position": [
      -4,
      5
    ],
    "facing": "south"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "bike": {
      "position": [
        -2,
        3
      ],
      "facing": "-y"
    },
    "pan": {
      "position": [
        1,
        5
      ],
      "facing": "+y"
    },
    "desklamp": {
      "position": [
        -3,
        5
      ],
      "facing": "-x"
    }
  }
}
🎯 Ground Truth
{
  "bike": {
    "position": [
      -1,
      2
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      1,
      4
    ],
    "facing": "west"
  },
  "desklamp": {
    "position": [
      -4,
      5
    ],
    "facing": "south"
  }
}
🧠 Cognitive Map Metrics
Global:
dir: 0.909
facing: 0.111
pos: 0.894
overall: 0.638
Global (Full):
dir: 0.500
facing: 0.083
pos: 0.656
overall: 0.413
Local:
dir: 1
facing: 1
pos: 0.867
overall: 0.956
Local (Newly):
dir: 1
facing: 1
pos: 0.867
overall: 0.956
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: 0.471
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: [Rotate(90), Observe()]
📊 Cognitive Map JSONs
🤖 Predicted
{
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "blue door": {
    "position": [
      4,
      -4
    ]
  },
  "yellow door": {
    "position": [
      5,
      -1
    ]
  },
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "south"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "south"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "north"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      1,
      -6
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      -2,
      -2
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -7
    ],
    "facing": "west"
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "shoes": {
      "position": [
        0,
        3
      ],
      "facing": "-x"
    },
    "rubberduck": {
      "position": [
        -1,
        3
      ],
      "facing": "+y"
    },
    "alarmclock": {
      "position": [
        -1,
        5
      ],
      "facing": "-x"
    },
    "yellow door": {
      "position": [
        2,
        3
      ]
    }
  }
}
🎯 Ground Truth
{
  "yellow door": {
    "position": [
      2,
      3
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      -2,
      3
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      -2,
      5
    ],
    "facing": "west"
  },
  "shoes": {
    "position": [
      0,
      3
    ],
    "facing": "west"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "shoes": {
      "position": [
        0,
        3
      ],
      "facing": "-x"
    },
    "rubberduck": {
      "position": [
        -1,
        3
      ],
      "facing": "+y"
    },
    "alarmclock": {
      "position": [
        -1,
        5
      ],
      "facing": "-x"
    },
    "yellow door": {
      "position": [
        2,
        3
      ]
    }
  }
}
🎯 Ground Truth
(no data)
🧠 Cognitive Map Metrics
Global:
dir: 0.909
facing: 0.111
pos: 0.894
overall: 0.638
Global (Full):
dir: 0.500
facing: 0.083
pos: 0.656
overall: 0.413
Local:
dir: 0.900
facing: 1
pos: 0.916
overall: 0.939
Local (Newly):
(none)
Fog Probe:
(none)
📈 Turn Metrics
node_coverage: 0.714
edge_coverage: 0.341
is_action_fail: False
step: 6
action_counts:
move: 1
rotate: 4
return: 0
observe: 6
term: 0
forced_term: 0
query: 0
information_gain: 0.614
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: [JumpTo(yellow door), Observe()]
📊 Cognitive Map JSONs
🤖 Predicted
{
  "agent": {
    "position": [
      7,
      -1
    ],
    "facing": "north"
  },
  "blue door": {
    "position": [
      5,
      -4
    ]
  },
  "yellow door": {
    "position": [
      7,
      -1
    ]
  },
  "shoes": {
    "position": [
      5,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      4,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      4,
      1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      5,
      -10
    ],
    "facing": "south"
  },
  "red chair": {
    "position": [
      3,
      -7
    ],
    "facing": "south"
  },
  "bike": {
    "position": [
      2,
      -6
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "desklamp": {
    "position": [
      0,
      -7
    ],
    "facing": "south"
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "north"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "north"
  }
}
📊 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
################
#########...C..#
#########......#
##......#......#
##......#AF...E#
##......#......#
##......*D....B#
##......########
##......########
######+#########
#......#########
#......#########
#......#########
#......#########
#......#########
#......#########
################
🔍 Fog Probe JSONs
📍 Candidates: A, B, C, D, E, F
🤖 Predicted: A, B, C, E, F
🎯 Ground Truth: E, B, D
🧠 Cognitive Map Metrics
Global:
dir: 0.879
facing: 1
pos: 0.853
overall: 0.911
Global (Full):
dir: 0.483
facing: 0.750
pos: 0.626
overall: 0.620
Local:
(none)
Local (Newly):
(none)
Fog Probe:
precision: 0.400
recall: 0.667
overall: 0.500
📈 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: 0.614
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(90), Observe()]
📊 Cognitive Map JSONs
🤖 Predicted
{
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ]
  },
  "blue door": {
    "position": [
      4,
      -4
    ]
  },
  "shoes": {
    "position": [
      5,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      3,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      3,
      0
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "bike": {
    "position": [
      1,
      -6
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      -1,
      -1
    ],
    "facing": "west"
  },
  "desklamp": {
    "position": [
      -1,
      -7
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      9,
      0
    ]
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      11,
      1
    ],
    "facing": "north"
  },
  "airplane": {
    "position": [
      11,
      2
    ],
    "facing": "south"
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "books": {
      "position": [
        0,
        4
      ]
    },
    "laptop": {
      "position": [
        -2,
        4
      ],
      "facing": "+y"
    },
    "backpack": {
      "position": [
        -2,
        6
      ],
      "facing": "-x"
    },
    "airplane": {
      "position": [
        -4,
        6
      ],
      "facing": "+x"
    }
  }
}
🎯 Ground Truth
{
  "airplane": {
    "position": [
      -4,
      6
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      -2,
      4
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -2,
      6
    ],
    "facing": "north"
  },
  "books": {
    "position": [
      0,
      4
    ],
    "facing": "east"
  }
}
📊 Cognitive Map JSONs
🤖 Predicted
{
  "origin": "agent",
  "objects": {
    "books": {
      "position": [
        0,
        4
      ]
    },
    "laptop": {
      "position": [
        -2,
        4
      ],
      "facing": "+y"
    },
    "backpack": {
      "position": [
        -2,
        6
      ],
      "facing": "-x"
    },
    "airplane": {
      "position": [
        -4,
        6
      ],
      "facing": "+x"
    }
  }
}
🎯 Ground Truth
{
  "airplane": {
    "position": [
      -4,
      6
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      -2,
      4
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      -2,
      6
    ],
    "facing": "north"
  },
  "books": {
    "position": [
      0,
      4
    ],
    "facing": "east"
  }
}
🧠 Cognitive Map Metrics
Global:
dir: 0.867
facing: 1
pos: 0.876
overall: 0.914
Global (Full):
dir: 0.867
facing: 1
pos: 0.876
overall: 0.914
Local:
dir: 1
facing: 1
pos: 1
overall: 1
Local (Newly):
dir: 1
facing: 1
pos: 1
overall: 1
Fog Probe:
(none)
📈 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: 0.874
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": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ]
  },
  "yellow door": {
    "position": [
      6,
      -1
    ]
  },
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "bike": {
    "position": [
      1,
      -6
    ],
    "facing": "east"
  },
  "pan": {
    "position": [
      -2,
      -3
    ],
    "facing": "west"
  },
  "desklamp": {
    "position": [
      -1,
      -7
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      9,
      -1
    ]
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "backpack": {
    "position": [
      11,
      1
    ],
    "facing": "north"
  },
  "airplane": {
    "position": [
      11,
      2
    ],
    "facing": "south"
  }
}
🎯 Ground Truth (Observed)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  }
}
🎯 Ground Truth (Full)
{
  "shoes": {
    "position": [
      4,
      -1
    ],
    "facing": "west"
  },
  "shoppingcart": {
    "position": [
      4,
      -9
    ],
    "facing": "south"
  },
  "laptop": {
    "position": [
      10,
      1
    ],
    "facing": "east"
  },
  "rubberduck": {
    "position": [
      2,
      -1
    ],
    "facing": "north"
  },
  "bike": {
    "position": [
      2,
      -5
    ],
    "facing": "east"
  },
  "airplane": {
    "position": [
      12,
      3
    ],
    "facing": "south"
  },
  "pan": {
    "position": [
      0,
      -3
    ],
    "facing": "west"
  },
  "alarmclock": {
    "position": [
      2,
      1
    ],
    "facing": "west"
  },
  "red chair": {
    "position": [
      2,
      -7
    ],
    "facing": "south"
  },
  "backpack": {
    "position": [
      12,
      1
    ],
    "facing": "north"
  },
  "desklamp": {
    "position": [
      -1,
      -8
    ],
    "facing": "south"
  },
  "books": {
    "position": [
      10,
      -1
    ],
    "facing": "east"
  },
  "yellow door": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  },
  "blue door": {
    "position": [
      4,
      -4
    ],
    "facing": "north"
  },
  "agent": {
    "position": [
      6,
      -1
    ],
    "facing": "east"
  }
}
🧠 Cognitive Map Metrics
Global:
dir: 0.958
facing: 1
pos: 0.899
overall: 0.953
Global (Full):
dir: 0.958
facing: 1
pos: 0.899
overall: 0.953
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: 0.874
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: 0.939
facing: 1
pos: 0.900
overall: 0.946
🧾 False Belief Object Sets
all_objects: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
all_changed_objects: ['airplane', 'alarmclock', 'pan', 'red chair']
newly_observed_changed (this turn): []
unchanged_objects: ['backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
pred_changed_keys: []
pred_unchanged_keys: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', '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': 'red chair', 'ori': True}, {'name': 'pan', 'ori': True}, {'name': 'alarmclock', 'pos': True}, {'name': 'airplane', 'pos': True}]
reported_changes: []
newly_observed_changed_objects: []
newly_observed_unchanged_objects: []
Current state
State at Turn 1

🔄 FB Turn 11

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📈 Turn Metrics
reward: -0.100
is_done: False
is_valid_action: True
🧭 False Belief Cogmap Metrics
Changed: airplane:
dir: None
pos: 0.780
facing: None
overall: None
Retention: airplane:
dir: None
pos: 0.380
facing: None
overall: None
Unchanged (all):
dir: 0.909
facing: 1
pos: 0.836
overall: 0.915
🧾 False Belief Object Sets
all_objects: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
all_changed_objects: ['airplane', 'alarmclock', 'pan', 'red chair']
newly_observed_changed (this turn): ['airplane']
unchanged_objects: ['backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
pred_changed_keys: ['airplane']
pred_unchanged_keys: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', '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': 'red chair', 'ori': True}, {'name': 'pan', 'ori': True}, {'name': 'alarmclock', 'pos': True}, {'name': 'airplane', 'pos': True}]
reported_changes: []
newly_observed_changed_objects: ['airplane']
newly_observed_unchanged_objects: ['yellow door', 'rubberduck', 'shoes', 'blue door']
Previous state
State before Turn 2
Current state
State at Turn 2

🔄 FB Turn 12

💬 Assistant Action
Actions: [JumpTo(blue door), Rotate(90), Observe()]
📈 Turn Metrics
reward: -0.100
is_done: False
is_valid_action: True
🧭 False Belief Cogmap Metrics
Changed: red chair:
dir: None
pos: None
facing: 1
overall: None
Retention: red chair:
dir: None
pos: None
facing: 0
overall: None
Changed: alarmclock:
dir: None
pos: 0.758
facing: None
overall: None
Retention: alarmclock:
dir: None
pos: 0.287
facing: None
overall: None
Unchanged (all):
dir: 0.621
facing: 1
pos: 0.674
overall: 0.765
🧾 False Belief Object Sets
all_objects: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
all_changed_objects: ['airplane', 'alarmclock', 'pan', 'red chair']
newly_observed_changed (this turn): ['alarmclock', 'red chair']
unchanged_objects: ['backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
pred_changed_keys: ['alarmclock', 'red chair']
pred_unchanged_keys: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', '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': 'red chair', 'ori': True}, {'name': 'pan', 'ori': True}, {'name': 'alarmclock', 'pos': True}, {'name': 'airplane', 'pos': True}]
reported_changes: []
newly_observed_changed_objects: ['red chair', 'alarmclock']
newly_observed_unchanged_objects: ['shoppingcart']
Previous state
State before Turn 3
Current state
State at Turn 3

🔄 FB Turn 13

💬 Assistant Action
Actions: [Rotate(90), Observe()]
📈 Turn Metrics
reward: -0.100
is_done: False
is_valid_action: True
🧭 False Belief Cogmap Metrics
Changed: pan:
dir: None
pos: None
facing: 1
overall: None
Retention: pan:
dir: None
pos: None
facing: 0
overall: None
Unchanged (all):
dir: 0.970
facing: 1
pos: 0.937
overall: 0.969
🧾 False Belief Object Sets
all_objects: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
all_changed_objects: ['airplane', 'alarmclock', 'pan', 'red chair']
newly_observed_changed (this turn): ['pan']
unchanged_objects: ['backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'rubberduck', 'shoes', 'shoppingcart', 'yellow door']
pred_changed_keys: ['pan']
pred_unchanged_keys: ['airplane', 'alarmclock', 'backpack', 'bike', 'blue door', 'books', 'desklamp', 'laptop', 'pan', 'red chair', 'rubberduck', 'shoes', 'shoppingcart', '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': 'red chair', 'ori': True}, {'name': 'pan', 'ori': True}, {'name': 'alarmclock', 'pos': True}, {'name': 'airplane', 'pos': True}]
reported_changes: []
newly_observed_changed_objects: ['pan']
newly_observed_unchanged_objects: ['desklamp', 'bike']
Previous state
State before Turn 4
Current state
State at Turn 4

🔄 FB Turn 14

💬 Assistant Action
Actions: [Term(changes="airplane: position, alarmclock: position, red chair: orientation, pan: orientation")]
📈 Turn Metrics
reward: 1
is_done: True
is_valid_action: True
success: 1
🧭 False Belief Info
step: 5
correctly_identified_changes: 1
f1_overall: 1
f1_position: 1
f1_facing: 1
action_cost: 4
action_cost_after_seen: 0
ground_truth_changes: [{'name': 'red chair', 'ori': True}, {'name': 'pan', 'ori': True}, {'name': 'alarmclock', 'pos': True}, {'name': 'airplane', 'pos': True}]
reported_changes: [{'name': 'airplane', 'pos': True}, {'name': 'alarmclock', 'pos': True}, {'name': 'red chair', 'ori': True}, {'name': 'pan', 'ori': True}]
newly_observed_changed_objects: []
newly_observed_unchanged_objects: []
Previous state
State before Turn 5
Current state
State at Turn 5

📊 Evaluation (default)

📊 Task: DirectionEvaluationTask

Question 1 (ID: fd2887aae65af114)

✅ Evaluation Results
id: fd2887aae65af114
question: You return to your starting position and face north. From a Top-Down map, describe where backpack is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: north east, mid distance
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 0
evaluation_mode: default
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: 47e25a4138337ec9)

✅ Evaluation Results
id: 47e25a4138337ec9
question: You return to your starting position and face north. From a Top-Down map, describe where books is relative to pan. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: east, far
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: default
Evaluation state
Q2: DirectionEvaluationTask

Question 3 (ID: 05aacd3852716124)

✅ Evaluation Results
id: 05aacd3852716124
question: You return to your starting position and face north. From a Top-Down map, describe where desklamp is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: south west, far
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: default
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: dd32b518994cc0cd)

✅ Evaluation Results
id: dd32b518994cc0cd
question: Now you jump to rubberduck's direction, facing its direction. Describe where alarmclock 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: default
Evaluation state
Q1: PovEvaluationTask

Question 2 (ID: b3bd1bdceefdf76a)

✅ Evaluation Results
id: b3bd1bdceefdf76a
question: Now you jump to red chair's direction, facing its direction. Describe where shoppingcart is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near
action: None
answer: front-left, mid distance
task_type: PovEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: default
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 9f4070bd1a76781d)

✅ Evaluation Results
id: 9f4070bd1a76781d
question: Now you jump to laptop'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
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: e0bba9ba020fcf43)

✅ Evaluation Results
id: e0bba9ba020fcf43
question: Now you jump to an object's position, facing its direction. You observe that alarmclock is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: rubberduck
final_pos: [4, 10]
final_ori: [0, 1]
final_observation: [{'name': 'alarmclock', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 1
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: BackwardPovTextEvaluationTask
choices: []
kwargs:
(none)
name_match: True
view_match: True
score: 1
evaluation_mode: default
Evaluation state
Q1: BackwardPovTextEvaluationTask

Question 2 (ID: 5ee18081cd74702f)

✅ Evaluation Results
id: 5ee18081cd74702f
question: Now you jump to an object's position, facing its direction. You observe that airplane is front-left, mid distance, facing right; backpack is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: laptop
final_pos: [12, 12]
final_ori: [1, 0]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 3
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: BackwardPovTextEvaluationTask
choices: []
kwargs:
(none)
name_match: True
view_match: True
score: 1
evaluation_mode: default
Evaluation state
Q2: BackwardPovTextEvaluationTask

Question 3 (ID: 48ef54e966ae6b2b)

✅ Evaluation Results
id: 48ef54e966ae6b2b
question: Now you jump to an object's position, facing its direction. You observe that blue door is front-left, mid distance, on left wall. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: bike
final_pos: [4, 6]
final_ori: [1, 0]
final_observation: [{'name': 'blue door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on left wall'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 2
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 746bd0e0e6ba5a86)

✅ Evaluation Results
id: 746bd0e0e6ba5a86
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-left, mid distance. 3. Jump to the object at front-right, slightly far. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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
Q1: Action2ViewEvaluationTask

Question 2 (ID: dd857cdb010f8d2c)

✅ Evaluation Results
id: dd857cdb010f8d2c
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, slightly far. 3. Rotate(-180) 4. Jump to the object at front-left, mid distance. After executing the actions, what is the ego relation of desklamp relative to you? Answer format: <ego direction>, <distance> Example: front, near
action: None
answer: front-left, slightly far
task_type: Action2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: default
Evaluation state
Q2: Action2ViewEvaluationTask

Question 3 (ID: f648d1cc302e836a)

✅ Evaluation Results
id: f648d1cc302e836a
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, mid distance. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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: a64c44dde1456896)

✅ Evaluation Results
id: a64c44dde1456896
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: bike is at front-right, slightly far, facing right 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: [1, 3]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'blue door'], ['rotate', 180], ['jumpto', 'desklamp'], ['rotate', 90]]
final_observation: [{'name': 'bike', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: False
ori_match: False
final_pos: [6.0, 2.0]
final_ori: [-1, 0]
visible_match: False
score: 0
evaluation_mode: default
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: c61a5d692c908db6)

✅ Evaluation Results
id: c61a5d692c908db6
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: bike is at front, near, facing right; blue door is at front-right, mid distance, on front wall 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: [4, 4]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 180], ['jumpto', 'blue door'], ['jumpto', 'red chair'], ['rotate', 180]]
final_observation: [{'name': 'bike', 'direction': 'front', 'distance': 'near', 'orientation': 'facing right'}, {'name': 'blue door', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'on front wall'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: False
ori_match: True
final_pos: [6.0, 2.0]
final_ori: [0, 1]
visible_match: False
score: 0
evaluation_mode: default
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 84f10bed2583426f)

✅ Evaluation Results
id: 84f10bed2583426f
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: airplane is at front-left, slightly far, facing right; backpack is at front-slight-left, slightly far, facing left; laptop is at front-left, slightly far, facing forward 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: [8, 10]
final_ori: [1, 0]
room_id: [1, 3]
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos']]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'laptop', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: True
ori_match: False
final_pos: [8.0, 10.0]
final_ori: [0, -1]
visible_match: False
score: 0
evaluation_mode: default
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: d07c09cead29a5ab)

✅ Evaluation Results
id: d07c09cead29a5ab
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: backpack, books, shoppingcart, rubberduck. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[12, 1], [10, -1], [4, -9], [2, -1]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.963
threshold: 0.900
score: 0.963
evaluation_mode: default
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: c301d9dd74a52e57)

✅ Evaluation Results
id: c301d9dd74a52e57
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: laptop, alarmclock, desklamp, rubberduck, red chair. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, 1], [2, 1], [-1, -8], [2, -1], [2, -7]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.871
threshold: 0.900
score: 0.871
evaluation_mode: default
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 4ade2017a10e41fb)

✅ Evaluation Results
id: 4ade2017a10e41fb
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: books, shoppingcart, laptop, alarmclock, bike. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, -1], [4, -9], [10, 1], [2, 1], [2, -5]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.871
threshold: 0.900
score: 0.871
evaluation_mode: default
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: d41a4cb1c4ae88e8)

✅ Evaluation Results
id: d41a4cb1c4ae88e8
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: desklamp, rubberduck, shoppingcart. 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: ['desklamp', 'shoppingcart', 'rubberduck']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: default
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 35aed4a89a7998dd)

✅ Evaluation Results
id: 35aed4a89a7998dd
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: backpack, pan, rubberduck. 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: ['backpack', 'rubberduck', 'pan']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: default
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: 070834d55928c793)

✅ Evaluation Results
id: 070834d55928c793
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: backpack, rubberduck, shoppingcart. 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: ['backpack', 'rubberduck', 'shoppingcart']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: default
Evaluation state
Q3: RotEvaluationTask

📊 Task: RotDualEvaluationTask

Question 1 (ID: 51578be02150882b)

✅ Evaluation Results
id: 51578be02150882b
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: desklamp, shoppingcart, rubberduck 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
Q1: RotDualEvaluationTask

Question 2 (ID: a232cb4d3c853647)

✅ Evaluation Results
id: a232cb4d3c853647
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: backpack, rubberduck, pan 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
Q2: RotDualEvaluationTask

Question 3 (ID: 83fd00114d015923)

✅ Evaluation Results
id: 83fd00114d015923
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: backpack, rubberduck, shoppingcart 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
Q3: RotDualEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: 12e5714b691ffd9d)

✅ Evaluation Results
id: 12e5714b691ffd9d
question: Still treat your initial position as origin (0, 0) You move to (4, -2) and face north. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front, near
task_type: Action2LocationEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: default
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 37203b723cb2ed85)

✅ Evaluation Results
id: 37203b723cb2ed85
question: Still treat your initial position as origin (0, 0) You move to (4, 2) and face south. What is the egocentric relation of rubberduck? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front-right, mid distance
task_type: Action2LocationEvaluationTask
choices: []
kwargs:
(none)
score: 0
evaluation_mode: default
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 1e0d4b92e81bdd63)

✅ Evaluation Results
id: 1e0d4b92e81bdd63
question: Still treat your initial position as origin (0, 0) You move to (5, 0) and face west. What is the egocentric relation of pan? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front-left, slightly far
task_type: Action2LocationEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: default
Evaluation state
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 7eb7d98b38d92500)

✅ Evaluation Results
id: 7eb7d98b38d92500
question: You move to a new location and face north. You observe: shoes is at front, near, facing left; alarmclock is at front-left, mid distance, facing left 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: [4, -2]
final_pos: [6, 9]
final_ori: [0, 1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'shoes', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'alarmclock', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing left'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: Location2ActionTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: default
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: 4190e9e80fa5f994)

✅ Evaluation Results
id: 4190e9e80fa5f994
question: You move to a new location and face south. You observe: rubberduck is at front-right, mid distance, facing backward; blue door is at front, slightly far, on front wall; pan is at front-right, slightly far, facing right 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: [4, 2]
final_pos: [6, 13]
final_ori: [0, -1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'rubberduck', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'blue door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}, {'name': 'pan', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: Location2ActionTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.800
raw_score: 0.800
score: 0.800
evaluation_mode: default
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: e006710c90936706)

✅ Evaluation Results
id: e006710c90936706
question: You move to a new location and face west. You observe: pan is at front-left, slightly far, facing forward; alarmclock is at front-slight-right, mid distance, facing forward; rubberduck is at front-slight-left, mid distance, facing right 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: [5, 0]
final_pos: [7, 11]
final_ori: [-1, 0]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'pan', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}, {'name': 'alarmclock', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': 'facing forward'}, {'name': 'rubberduck', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: Location2ActionTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: default
Evaluation state
Q3: View2LocationTextEvaluationTask

📊 Evaluation (prompt_cogmap)

📊 Task: DirectionEvaluationTask

Question 1 (ID: fd2887aae65af114)

✅ Evaluation Results
id: fd2887aae65af114
question: You return to your starting position and face north. From a Top-Down map, describe where backpack is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: north east, mid distance
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: 47e25a4138337ec9)

✅ Evaluation Results
id: 47e25a4138337ec9
question: You return to your starting position and face north. From a Top-Down map, describe where books is relative to pan. 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
Q2: DirectionEvaluationTask

Question 3 (ID: 05aacd3852716124)

✅ Evaluation Results
id: 05aacd3852716124
question: You return to your starting position and face north. From a Top-Down map, describe where desklamp is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: south west, far
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: dd32b518994cc0cd)

✅ Evaluation Results
id: dd32b518994cc0cd
question: Now you jump to rubberduck's direction, facing its direction. Describe where alarmclock 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: prompt_cogmap
Evaluation state
Q1: PovEvaluationTask

Question 2 (ID: b3bd1bdceefdf76a)

✅ Evaluation Results
id: b3bd1bdceefdf76a
question: Now you jump to red chair's direction, facing its direction. Describe where shoppingcart is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near
action: None
answer: front-left, mid distance
task_type: PovEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 9f4070bd1a76781d)

✅ Evaluation Results
id: 9f4070bd1a76781d
question: Now you jump to laptop'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: prompt_cogmap
Evaluation state
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: e0bba9ba020fcf43)

✅ Evaluation Results
id: e0bba9ba020fcf43
question: Now you jump to an object's position, facing its direction. You observe that alarmclock is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: rubberduck
final_pos: [4, 10]
final_ori: [0, 1]
final_observation: [{'name': 'alarmclock', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 1
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 5ee18081cd74702f)

✅ Evaluation Results
id: 5ee18081cd74702f
question: Now you jump to an object's position, facing its direction. You observe that airplane is front-left, mid distance, facing right; backpack is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: laptop
final_pos: [12, 12]
final_ori: [1, 0]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 3
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 48ef54e966ae6b2b)

✅ Evaluation Results
id: 48ef54e966ae6b2b
question: Now you jump to an object's position, facing its direction. You observe that blue door is front-left, mid distance, on left wall. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: bike
final_pos: [4, 6]
final_ori: [1, 0]
final_observation: [{'name': 'blue door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on left wall'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 2
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: dd857cdb010f8d2c)

✅ Evaluation Results
id: dd857cdb010f8d2c
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, slightly far. 3. Rotate(-180) 4. Jump to the object at front-left, mid distance. After executing the actions, what is the ego relation of desklamp relative to you? Answer format: <ego direction>, <distance> Example: front, near
action: None
answer: front-left, slightly far
task_type: Action2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: prompt_cogmap
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: f648d1cc302e836a)

✅ Evaluation Results
id: f648d1cc302e836a
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, mid distance. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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: prompt_cogmap
Evaluation state
Q2: Action2ViewEvaluationTask

Question 3 (ID: 746bd0e0e6ba5a86)

✅ Evaluation Results
id: 746bd0e0e6ba5a86
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-left, mid distance. 3. Jump to the object at front-right, slightly far. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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: prompt_cogmap
Evaluation state
Q3: Action2ViewEvaluationTask

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: a64c44dde1456896)

✅ Evaluation Results
id: a64c44dde1456896
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: bike is at front-right, slightly far, facing right 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: [1, 3]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'blue door'], ['rotate', 180], ['jumpto', 'desklamp'], ['rotate', 90]]
final_observation: [{'name': 'bike', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: False
ori_match: False
final_pos: [6.0, 7.0]
final_ori: [0, -1]
visible_match: False
score: 0
evaluation_mode: prompt_cogmap
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: c61a5d692c908db6)

✅ Evaluation Results
id: c61a5d692c908db6
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: bike is at front, near, facing right; blue door is at front-right, mid distance, on front wall 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: [4, 4]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 180], ['jumpto', 'blue door'], ['jumpto', 'red chair'], ['rotate', 180]]
final_observation: [{'name': 'bike', 'direction': 'front', 'distance': 'near', 'orientation': 'facing right'}, {'name': 'blue door', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'on front wall'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: False
ori_match: True
final_pos: [6.0, 2.0]
final_ori: [0, 1]
visible_match: False
score: 0
evaluation_mode: prompt_cogmap
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 84f10bed2583426f)

✅ Evaluation Results
id: 84f10bed2583426f
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: airplane is at front-left, slightly far, facing right; backpack is at front-slight-left, slightly far, facing left; laptop is at front-left, slightly far, facing forward 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: [8, 10]
final_ori: [1, 0]
room_id: [1, 3]
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos']]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'laptop', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: True
ori_match: True
final_pos: [8.0, 10.0]
final_ori: [1, 0]
visible_match: True
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: d07c09cead29a5ab)

✅ Evaluation Results
id: d07c09cead29a5ab
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: backpack, books, shoppingcart, rubberduck. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[12, 1], [10, -1], [4, -9], [2, -1]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.876
threshold: 0.900
score: 0.876
evaluation_mode: prompt_cogmap
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: c301d9dd74a52e57)

✅ Evaluation Results
id: c301d9dd74a52e57
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: laptop, alarmclock, desklamp, rubberduck, red chair. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, 1], [2, 1], [-1, -8], [2, -1], [2, -7]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.646
threshold: 0.900
score: 0.646
evaluation_mode: prompt_cogmap
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 4ade2017a10e41fb)

✅ Evaluation Results
id: 4ade2017a10e41fb
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: books, shoppingcart, laptop, alarmclock, bike. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, -1], [4, -9], [10, 1], [2, 1], [2, -5]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.963
threshold: 0.900
score: 0.963
evaluation_mode: prompt_cogmap
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: d41a4cb1c4ae88e8)

✅ Evaluation Results
id: d41a4cb1c4ae88e8
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: desklamp, rubberduck, shoppingcart. 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: ['desklamp', 'shoppingcart', 'rubberduck']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 35aed4a89a7998dd)

✅ Evaluation Results
id: 35aed4a89a7998dd
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: backpack, pan, rubberduck. 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: ['backpack', 'rubberduck', 'pan']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: 070834d55928c793)

✅ Evaluation Results
id: 070834d55928c793
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: backpack, rubberduck, shoppingcart. 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: ['backpack', 'rubberduck', 'shoppingcart']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q3: RotEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: 12e5714b691ffd9d)

✅ Evaluation Results
id: 12e5714b691ffd9d
question: Still treat your initial position as origin (0, 0) You move to (4, -2) and face north. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front, near
task_type: Location2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 37203b723cb2ed85)

✅ Evaluation Results
id: 37203b723cb2ed85
question: Still treat your initial position as origin (0, 0) You move to (4, 2) and face south. What is the egocentric relation of rubberduck? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front-right, mid distance
task_type: Location2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: prompt_cogmap
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 1e0d4b92e81bdd63)

✅ Evaluation Results
id: 1e0d4b92e81bdd63
question: Still treat your initial position as origin (0, 0) You move to (5, 0) and face west. What is the egocentric relation of pan? 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
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 7eb7d98b38d92500)

✅ Evaluation Results
id: 7eb7d98b38d92500
question: You move to a new location and face north. You observe: shoes is at front, near, facing left; alarmclock is at front-left, mid distance, facing left 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: [4, -2]
final_pos: [6, 9]
final_ori: [0, 1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'shoes', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'alarmclock', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing left'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: 4190e9e80fa5f994)

✅ Evaluation Results
id: 4190e9e80fa5f994
question: You move to a new location and face south. You observe: rubberduck is at front-right, mid distance, facing backward; blue door is at front, slightly far, on front wall; pan is at front-right, slightly far, facing right 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: [4, 2]
final_pos: [6, 13]
final_ori: [0, -1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'rubberduck', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'blue door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}, {'name': 'pan', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.800
raw_score: 0.800
score: 0.800
evaluation_mode: prompt_cogmap
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: e006710c90936706)

✅ Evaluation Results
id: e006710c90936706
question: You move to a new location and face west. You observe: pan is at front-left, slightly far, facing forward; alarmclock is at front-slight-right, mid distance, facing forward; rubberduck is at front-slight-left, mid distance, facing right 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: [5, 0]
final_pos: [7, 11]
final_ori: [-1, 0]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'pan', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}, {'name': 'alarmclock', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': 'facing forward'}, {'name': 'rubberduck', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: prompt_cogmap
Evaluation state
Q3: View2LocationTextEvaluationTask

📊 Evaluation (use_gt_cogmap)

📊 Task: DirectionEvaluationTask

Question 1 (ID: fd2887aae65af114)

✅ Evaluation Results
id: fd2887aae65af114
question: You return to your starting position and face north. From a Top-Down map, describe where backpack is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: north east, mid distance
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: 47e25a4138337ec9)

✅ Evaluation Results
id: 47e25a4138337ec9
question: You return to your starting position and face north. From a Top-Down map, describe where books is relative to pan. 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
Q2: DirectionEvaluationTask

Question 3 (ID: 05aacd3852716124)

✅ Evaluation Results
id: 05aacd3852716124
question: You return to your starting position and face north. From a Top-Down map, describe where desklamp is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: south west, far
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: dd32b518994cc0cd)

✅ Evaluation Results
id: dd32b518994cc0cd
question: Now you jump to rubberduck's direction, facing its direction. Describe where alarmclock 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: b3bd1bdceefdf76a)

✅ Evaluation Results
id: b3bd1bdceefdf76a
question: Now you jump to red chair's direction, facing its direction. Describe where shoppingcart is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near
action: None
answer: front-left, mid distance
task_type: PovEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 9f4070bd1a76781d)

✅ Evaluation Results
id: 9f4070bd1a76781d
question: Now you jump to laptop'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
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: e0bba9ba020fcf43)

✅ Evaluation Results
id: e0bba9ba020fcf43
question: Now you jump to an object's position, facing its direction. You observe that alarmclock is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: rubberduck
final_pos: [4, 10]
final_ori: [0, 1]
final_observation: [{'name': 'alarmclock', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 1
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 5ee18081cd74702f)

✅ Evaluation Results
id: 5ee18081cd74702f
question: Now you jump to an object's position, facing its direction. You observe that airplane is front-left, mid distance, facing right; backpack is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: laptop
final_pos: [12, 12]
final_ori: [1, 0]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 3
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 48ef54e966ae6b2b)

✅ Evaluation Results
id: 48ef54e966ae6b2b
question: Now you jump to an object's position, facing its direction. You observe that blue door is front-left, mid distance, on left wall. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: bike
final_pos: [4, 6]
final_ori: [1, 0]
final_observation: [{'name': 'blue door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on left wall'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 2
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: dd857cdb010f8d2c)

✅ Evaluation Results
id: dd857cdb010f8d2c
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, slightly far. 3. Rotate(-180) 4. Jump to the object at front-left, mid distance. After executing the actions, what is the ego relation of desklamp relative to you? Answer format: <ego direction>, <distance> Example: front, near
action: None
answer: front-left, slightly far
task_type: Action2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: f648d1cc302e836a)

✅ Evaluation Results
id: f648d1cc302e836a
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, mid distance. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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
Q2: Action2ViewEvaluationTask

Question 3 (ID: 746bd0e0e6ba5a86)

✅ Evaluation Results
id: 746bd0e0e6ba5a86
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-left, mid distance. 3. Jump to the object at front-right, slightly far. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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: a64c44dde1456896)

✅ Evaluation Results
id: a64c44dde1456896
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: bike is at front-right, slightly far, facing right 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: [1, 3]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'blue door'], ['rotate', 180], ['jumpto', 'desklamp'], ['rotate', 90]]
final_observation: [{'name': 'bike', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
error: target_not_visible
score: 0
evaluation_mode: use_gt_cogmap
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: c61a5d692c908db6)

✅ Evaluation Results
id: c61a5d692c908db6
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: bike is at front, near, facing right; blue door is at front-right, mid distance, on front wall 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: [4, 4]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 180], ['jumpto', 'blue door'], ['jumpto', 'red chair'], ['rotate', 180]]
final_observation: [{'name': 'bike', 'direction': 'front', 'distance': 'near', 'orientation': 'facing right'}, {'name': 'blue door', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'on front wall'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: True
ori_match: True
final_pos: [4.0, 4.0]
final_ori: [0, 1]
visible_match: True
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 84f10bed2583426f)

✅ Evaluation Results
id: 84f10bed2583426f
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: airplane is at front-left, slightly far, facing right; backpack is at front-slight-left, slightly far, facing left; laptop is at front-left, slightly far, facing forward 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: [8, 10]
final_ori: [1, 0]
room_id: [1, 3]
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos']]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'laptop', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: True
ori_match: True
final_pos: [8.0, 10.0]
final_ori: [1, 0]
visible_match: True
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: d07c09cead29a5ab)

✅ Evaluation Results
id: d07c09cead29a5ab
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: backpack, books, shoppingcart, rubberduck. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[12, 1], [10, -1], [4, -9], [2, -1]]
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: c301d9dd74a52e57)

✅ Evaluation Results
id: c301d9dd74a52e57
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: laptop, alarmclock, desklamp, rubberduck, red chair. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, 1], [2, 1], [-1, -8], [2, -1], [2, -7]]
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: 4ade2017a10e41fb)

✅ Evaluation Results
id: 4ade2017a10e41fb
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: books, shoppingcart, laptop, alarmclock, bike. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, -1], [4, -9], [10, 1], [2, 1], [2, -5]]
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: d41a4cb1c4ae88e8)

✅ Evaluation Results
id: d41a4cb1c4ae88e8
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: desklamp, rubberduck, shoppingcart. 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: ['desklamp', 'shoppingcart', 'rubberduck']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 35aed4a89a7998dd)

✅ Evaluation Results
id: 35aed4a89a7998dd
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: backpack, pan, rubberduck. 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: ['backpack', 'rubberduck', 'pan']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: 070834d55928c793)

✅ Evaluation Results
id: 070834d55928c793
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: backpack, rubberduck, shoppingcart. 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: ['backpack', 'rubberduck', 'shoppingcart']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q3: RotEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: 12e5714b691ffd9d)

✅ Evaluation Results
id: 12e5714b691ffd9d
question: Still treat your initial position as origin (0, 0) You move to (4, -2) and face north. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front, near
task_type: Location2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 37203b723cb2ed85)

✅ Evaluation Results
id: 37203b723cb2ed85
question: Still treat your initial position as origin (0, 0) You move to (4, 2) and face south. What is the egocentric relation of rubberduck? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front-right, mid distance
task_type: Location2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_gt_cogmap
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 1e0d4b92e81bdd63)

✅ Evaluation Results
id: 1e0d4b92e81bdd63
question: Still treat your initial position as origin (0, 0) You move to (5, 0) and face west. What is the egocentric relation of pan? 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
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 7eb7d98b38d92500)

✅ Evaluation Results
id: 7eb7d98b38d92500
question: You move to a new location and face north. You observe: shoes is at front, near, facing left; alarmclock is at front-left, mid distance, facing left 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: [4, -2]
final_pos: [6, 9]
final_ori: [0, 1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'shoes', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'alarmclock', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing left'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 4190e9e80fa5f994)

✅ Evaluation Results
id: 4190e9e80fa5f994
question: You move to a new location and face south. You observe: rubberduck is at front-right, mid distance, facing backward; blue door is at front, slightly far, on front wall; pan is at front-right, slightly far, facing right 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: [4, 2]
final_pos: [6, 13]
final_ori: [0, -1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'rubberduck', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'blue door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}, {'name': 'pan', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.800
raw_score: 0.800
score: 0.800
evaluation_mode: use_gt_cogmap
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: e006710c90936706)

✅ Evaluation Results
id: e006710c90936706
question: You move to a new location and face west. You observe: pan is at front-left, slightly far, facing forward; alarmclock is at front-slight-right, mid distance, facing forward; rubberduck is at front-slight-left, mid distance, facing right 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: [5, 0]
final_pos: [7, 11]
final_ori: [-1, 0]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'pan', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}, {'name': 'alarmclock', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': 'facing forward'}, {'name': 'rubberduck', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: fd2887aae65af114)

✅ Evaluation Results
id: fd2887aae65af114
question: You return to your starting position and face north. From a Top-Down map, describe where backpack is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: north east, mid distance
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q1: DirectionEvaluationTask

Question 2 (ID: 47e25a4138337ec9)

✅ Evaluation Results
id: 47e25a4138337ec9
question: You return to your starting position and face north. From a Top-Down map, describe where books is relative to pan. 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
Q2: DirectionEvaluationTask

Question 3 (ID: 05aacd3852716124)

✅ Evaluation Results
id: 05aacd3852716124
question: You return to your starting position and face north. From a Top-Down map, describe where desklamp is relative to books. Answer format: <cardinal direction>, <distance> Example: north-west, near
action: None
answer: south west, far
task_type: DirectionEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q3: DirectionEvaluationTask

📊 Task: PovEvaluationTask

Question 1 (ID: dd32b518994cc0cd)

✅ Evaluation Results
id: dd32b518994cc0cd
question: Now you jump to rubberduck's direction, facing its direction. Describe where alarmclock 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: b3bd1bdceefdf76a)

✅ Evaluation Results
id: b3bd1bdceefdf76a
question: Now you jump to red chair's direction, facing its direction. Describe where shoppingcart is relative to you. Answer format: <ego direction>, <distance> Example: front-left, near
action: None
answer: front-left, mid distance
task_type: PovEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q2: PovEvaluationTask

Question 3 (ID: 9f4070bd1a76781d)

✅ Evaluation Results
id: 9f4070bd1a76781d
question: Now you jump to laptop'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
Q3: PovEvaluationTask

📊 Task: BackwardPovTextEvaluationTask

Question 1 (ID: e0bba9ba020fcf43)

✅ Evaluation Results
id: e0bba9ba020fcf43
question: Now you jump to an object's position, facing its direction. You observe that alarmclock is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: rubberduck
final_pos: [4, 10]
final_ori: [0, 1]
final_observation: [{'name': 'alarmclock', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 1
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 5ee18081cd74702f)

✅ Evaluation Results
id: 5ee18081cd74702f
question: Now you jump to an object's position, facing its direction. You observe that airplane is front-left, mid distance, facing right; backpack is front, near, facing left. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: laptop
final_pos: [12, 12]
final_ori: [1, 0]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 3
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: 48ef54e966ae6b2b)

✅ Evaluation Results
id: 48ef54e966ae6b2b
question: Now you jump to an object's position, facing its direction. You observe that blue door is front-left, mid distance, on left wall. Which object are you standing at? Answer format: <object_name> Example: lamp
action: None
answer:
answer: bike
final_pos: [4, 6]
final_ori: [1, 0]
final_observation: [{'name': 'blue door', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'on left wall'}]
object_positions:
shoes: [6.0, 10.0]
shoppingcart: [6.0, 2.0]
laptop: [12.0, 12.0]
rubberduck: [4.0, 10.0]
bike: [4.0, 6.0]
airplane: [14.0, 14.0]
pan: [2.0, 8.0]
alarmclock: [4.0, 12.0]
red chair: [4.0, 4.0]
backpack: [14.0, 12.0]
desklamp: [1.0, 3.0]
books: [12.0, 10.0]
yellow door: [8.0, 10.0]
blue door: [6.0, 7.0]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
room_id: 2
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
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: dd857cdb010f8d2c)

✅ Evaluation Results
id: dd857cdb010f8d2c
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, slightly far. 3. Rotate(-180) 4. Jump to the object at front-left, mid distance. After executing the actions, what is the ego relation of desklamp relative to you? Answer format: <ego direction>, <distance> Example: front, near
action: None
answer: front-left, slightly far
task_type: Action2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: use_model_cogmap
Evaluation state
Q1: Action2ViewEvaluationTask

Question 2 (ID: f648d1cc302e836a)

✅ Evaluation Results
id: f648d1cc302e836a
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, mid distance. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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
Q2: Action2ViewEvaluationTask

Question 3 (ID: 746bd0e0e6ba5a86)

✅ Evaluation Results
id: 746bd0e0e6ba5a86
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-left, mid distance. 3. Jump to the object at front-right, slightly far. 4. Rotate(-180) After executing the actions, what is the ego relation of shoes 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: use_model_cogmap
Evaluation state
Q3: Action2ViewEvaluationTask

📊 Task: View2ActionTextEvaluationTask

Question 1 (ID: a64c44dde1456896)

✅ Evaluation Results
id: a64c44dde1456896
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: bike is at front-right, slightly far, facing right 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: [1, 3]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'blue door'], ['rotate', 180], ['jumpto', 'desklamp'], ['rotate', 90]]
final_observation: [{'name': 'bike', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: True
ori_match: True
final_pos: [1.0, 3.0]
final_ori: [0, 1]
visible_match: True
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q1: View2ActionTextEvaluationTask

Question 2 (ID: c61a5d692c908db6)

✅ Evaluation Results
id: c61a5d692c908db6
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: bike is at front, near, facing right; blue door is at front-right, mid distance, on front wall 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: [4, 4]
final_ori: [0, 1]
room_id: 2
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 180], ['jumpto', 'blue door'], ['jumpto', 'red chair'], ['rotate', 180]]
final_observation: [{'name': 'bike', 'direction': 'front', 'distance': 'near', 'orientation': 'facing right'}, {'name': 'blue door', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'on front wall'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: False
ori_match: True
final_pos: [1.0, 3.0]
final_ori: [0, 1]
visible_match: False
score: 0
evaluation_mode: use_model_cogmap
Evaluation state
Q2: View2ActionTextEvaluationTask

Question 3 (ID: 84f10bed2583426f)

✅ Evaluation Results
id: 84f10bed2583426f
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: airplane is at front-left, slightly far, facing right; backpack is at front-slight-left, slightly far, facing left; laptop is at front-left, slightly far, facing forward 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: [8, 10]
final_ori: [1, 0]
room_id: [1, 3]
init_pos: [2, 11]
init_ori: [0, 1]
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
minimal_plan: [['rotate', 90], ['jumpto', 'initial_pos']]
final_observation: [{'name': 'airplane', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing right'}, {'name': 'backpack', 'direction': 'front-slight-left', 'distance': 'slightly far', 'orientation': 'facing left'}, {'name': 'laptop', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}]
task_type: View2ActionTextEvaluationTask
choices: []
kwargs:
(none)
pos_match: True
ori_match: True
final_pos: [8.0, 10.0]
final_ori: [1, 0]
visible_match: True
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q3: View2ActionTextEvaluationTask

📊 Task: AlloMappingEvaluationTask

Question 1 (ID: d07c09cead29a5ab)

✅ Evaluation Results
id: d07c09cead29a5ab
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: backpack, books, shoppingcart, rubberduck. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[12, 1], [10, -1], [4, -9], [2, -1]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.963
threshold: 0.900
score: 0.963
evaluation_mode: use_model_cogmap
Evaluation state
Q1: AlloMappingEvaluationTask

Question 2 (ID: c301d9dd74a52e57)

✅ Evaluation Results
id: c301d9dd74a52e57
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: laptop, alarmclock, desklamp, rubberduck, red chair. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, 1], [2, 1], [-1, -8], [2, -1], [2, -7]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.968
threshold: 0.900
score: 0.968
evaluation_mode: use_model_cogmap
Evaluation state
Q2: AlloMappingEvaluationTask

Question 3 (ID: 4ade2017a10e41fb)

✅ Evaluation Results
id: 4ade2017a10e41fb
question: Treat your starting position as the origin (0, 0) while facing north. Report allocentric coordinates using (x right/east, y up/north). Objects: books, shoppingcart, laptop, alarmclock, bike. Answer format: (x0, y0); (x1, y1); ... in the same order. Example: (1, 0); (-2, 3); (0, -1)
action: None
answer: [[10, -1], [4, -9], [10, 1], [2, 1], [2, -5]]
task_type: AlloMappingEvaluationTask
choices: []
kwargs:
(none)
similarity: 0.921
threshold: 0.900
score: 0.921
evaluation_mode: use_model_cogmap
Evaluation state
Q3: AlloMappingEvaluationTask

📊 Task: RotEvaluationTask

Question 1 (ID: d41a4cb1c4ae88e8)

✅ Evaluation Results
id: d41a4cb1c4ae88e8
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: desklamp, rubberduck, shoppingcart. 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: ['desklamp', 'shoppingcart', 'rubberduck']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q1: RotEvaluationTask

Question 2 (ID: 35aed4a89a7998dd)

✅ Evaluation Results
id: 35aed4a89a7998dd
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: backpack, pan, rubberduck. 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: ['backpack', 'rubberduck', 'pan']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q2: RotEvaluationTask

Question 3 (ID: 070834d55928c793)

✅ Evaluation Results
id: 070834d55928c793
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: backpack, rubberduck, shoppingcart. 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: ['backpack', 'rubberduck', 'shoppingcart']
task_type: RotEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q3: RotEvaluationTask

📊 Task: Location2ViewEvaluationTask

Question 1 (ID: 12e5714b691ffd9d)

✅ Evaluation Results
id: 12e5714b691ffd9d
question: Still treat your initial position as origin (0, 0) You move to (4, -2) and face north. What is the egocentric relation of shoes? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front, near
task_type: Location2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q1: Location2ViewEvaluationTask

Question 2 (ID: 37203b723cb2ed85)

✅ Evaluation Results
id: 37203b723cb2ed85
question: Still treat your initial position as origin (0, 0) You move to (4, 2) and face south. What is the egocentric relation of rubberduck? Answer format: <direction>, <distance> Example: front, near
action: None
answer: front-right, mid distance
task_type: Location2ViewEvaluationTask
choices: []
kwargs:
(none)
score: 0.500
evaluation_mode: use_model_cogmap
Evaluation state
Q2: Location2ViewEvaluationTask

Question 3 (ID: 1e0d4b92e81bdd63)

✅ Evaluation Results
id: 1e0d4b92e81bdd63
question: Still treat your initial position as origin (0, 0) You move to (5, 0) and face west. What is the egocentric relation of pan? 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
Q3: Location2ViewEvaluationTask

📊 Task: View2LocationTextEvaluationTask

Question 1 (ID: 7eb7d98b38d92500)

✅ Evaluation Results
id: 7eb7d98b38d92500
question: You move to a new location and face north. You observe: shoes is at front, near, facing left; alarmclock is at front-left, mid distance, facing left 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: [4, -2]
final_pos: [6, 9]
final_ori: [0, 1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'shoes', 'direction': 'front', 'distance': 'near', 'orientation': 'facing left'}, {'name': 'alarmclock', 'direction': 'front-left', 'distance': 'mid distance', 'orientation': 'facing left'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q1: View2LocationTextEvaluationTask

Question 2 (ID: 4190e9e80fa5f994)

✅ Evaluation Results
id: 4190e9e80fa5f994
question: You move to a new location and face south. You observe: rubberduck is at front-right, mid distance, facing backward; blue door is at front, slightly far, on front wall; pan is at front-right, slightly far, facing right 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: [4, 2]
final_pos: [6, 13]
final_ori: [0, -1]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'rubberduck', 'direction': 'front-right', 'distance': 'mid distance', 'orientation': 'facing backward'}, {'name': 'blue door', 'direction': 'front', 'distance': 'slightly far', 'orientation': 'on front wall'}, {'name': 'pan', 'direction': 'front-right', 'distance': 'slightly far', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q2: View2LocationTextEvaluationTask

Question 3 (ID: e006710c90936706)

✅ Evaluation Results
id: e006710c90936706
question: You move to a new location and face west. You observe: pan is at front-left, slightly far, facing forward; alarmclock is at front-slight-right, mid distance, facing forward; rubberduck is at front-slight-left, mid distance, facing right 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: [5, 0]
final_pos: [7, 11]
final_ori: [-1, 0]
room_id: 1
object_positions:
shoes: [6, 10]
shoppingcart: [6, 2]
laptop: [12, 12]
rubberduck: [4, 10]
bike: [4, 6]
airplane: [14, 14]
pan: [2, 8]
alarmclock: [4, 12]
red chair: [4, 4]
backpack: [14, 12]
desklamp: [1, 3]
books: [12, 10]
yellow door: [8, 10]
blue door: [6, 7]
object_orientations:
shoes: [-1, 0]
shoppingcart: [0, -1]
laptop: [1, 0]
rubberduck: [0, 1]
bike: [1, 0]
airplane: [0, -1]
pan: [-1, 0]
alarmclock: [-1, 0]
red chair: [0, -1]
backpack: [0, 1]
desklamp: [0, -1]
yellow door: [1, 0]
blue door: [0, 1]
final_observation: [{'name': 'pan', 'direction': 'front-left', 'distance': 'slightly far', 'orientation': 'facing forward'}, {'name': 'alarmclock', 'direction': 'front-slight-right', 'distance': 'mid distance', 'orientation': 'facing forward'}, {'name': 'rubberduck', 'direction': 'front-slight-left', 'distance': 'mid distance', 'orientation': 'facing right'}]
gate_info:
yellow door:
room_ids: [1, 3]
ori_by_room:
1: [-1, 0]
3: [1, 0]
blue door:
room_ids: [2, 1]
ori_by_room:
2: [0, -1]
1: [0, 1]
object_rooms:
shoes: 1
shoppingcart: 2
laptop: 3
rubberduck: 1
bike: 2
airplane: 3
pan: 1
alarmclock: 1
red chair: 2
backpack: 3
desklamp: 2
books: 3
yellow door: [1, 3]
blue door: [2, 1]
task_type: View2LocationTextEvaluationTask
choices: []
kwargs:
(none)
similarity: 1
raw_score: 1
score: 1
evaluation_mode: use_model_cogmap
Evaluation state
Q3: View2LocationTextEvaluationTask