Upload experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence (part 5)

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4115.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4115,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: fan, table, sofa, window?",
+ "options": [
+  "A. sofa, fan, table, window",
+  "B. table, window, fan, sofa",
+  "C. sofa, window, fan, table",
+  "D. fan, table, sofa, window"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4116.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4116,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, trash bin, fan, sofa?",
+ "options": [
+  "A. table, trash bin, fan, sofa",
+  "B. sofa, trash bin, fan, table",
+  "C. fan, table, trash bin, sofa",
+  "D. table, trash bin, sofa, fan"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4117.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4117,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: fan, table, window, backpack?",
+ "options": [
+  "A. fan, table, backpack, window",
+  "B. fan, table, window, backpack",
+  "C. backpack, window, fan, table",
+  "D. table, window, fan, backpack"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4118.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4118,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, door, window, sofa?",
+ "options": [
+  "A. sofa, window, door, table",
+  "B. window, table, door, sofa",
+  "C. table, door, window, sofa",
+  "D. sofa, table, door, window"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4119.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4119,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: window, backpack, door, table?",
+ "options": [
+  "A. door, table, backpack, window",
+  "B. backpack, window, door, table",
+  "C. window, backpack, door, table",
+  "D. backpack, window, table, door"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "window": 0,
+   "backpack": 9,
+   "door": 2,
+   "table": 10
+  },
+  "true_order_per_spatial_code": "window, door, backpack, table",
+  "ground_truth_option_text": "backpack, window, door, table",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4120.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4120,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, trash bin, sofa, door?",
+ "options": [
+  "A. trash bin, table, sofa, door",
+  "B. table, trash bin, sofa, door",
+  "C. trash bin, door, sofa, table",
+  "D. sofa, trash bin, door, table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0,
+ "appearance_order_diagnosis": {
+  "diagnosable": true,
+  "class_positions_in_real_order": {
+   "table": 10,
+   "trash bin": 4,
+   "sofa": 8,
+   "door": 2
+  },
+  "true_order_per_spatial_code": "door, trash bin, sofa, table",
+  "ground_truth_option_text": "sofa, trash bin, door, table",
+  "matches_ground_truth": false,
+  "verdict": "the spatial code's real detected order genuinely disagrees with the official ground truth's ordering -- not an engine bug, the engine correctly read the real data it had"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4121.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4121,
+ "question_type": "obj_appearance_order",
+ "question": "What will be the first-time appearance order of the following categories in the video: table, window, backpack, printer?",
+ "options": [
+  "A. table, printer, backpack, window",
+  "B. table, window, backpack, printer",
+  "C. backpack, window, printer, table",
+  "D. backpack, printer, table, window"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4330.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4330,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the backpack and facing the fan, is the door to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. right",
+  "B. back",
+  "C. left"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4331.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4331,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the backpack and facing the door, is the fan to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. back",
+  "B. left",
+  "C. right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4332.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4332,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the fan and facing the backpack, is the door to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. left",
+  "B. back",
+  "C. right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4333.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4333,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the fan and facing the door, is the table to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. left",
+  "B. right",
+  "C. back"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4334.json

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+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4334,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the fan and facing the table, is the door to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. back",
+  "B. right",
+  "C. left"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4335.json

@@ -0,0 +1,24 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4335,
+ "question_type": "object_rel_direction_medium",
+ "question": "If I am standing by the door and facing the fan, is the table to my left, right, or back?\nAn object is to my back if I would have to turn at least 135 degrees in order to face it.",
+ "options": [
+  "A. back",
+  "B. right",
+  "C. left"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4536.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4536,
+ "question_type": "object_counting",
+ "question": "How many window(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2",
+ "answer_given": "3",
+ "answer_raw": "3",
+ "score": 0.1
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4537.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4537,
+ "question_type": "object_counting",
+ "question": "How many trash bin(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2",
+ "answer_given": "1",
+ "answer_raw": "1",
+ "score": 0.1
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4839.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4839,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the table and the door (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2.6",
+ "answer_given": "1.7",
+ "answer_raw": "1.7",
+ "score": 0.4
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4840.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4840,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the door and the fan (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2.4",
+ "answer_given": "2.66",
+ "answer_raw": "2.66",
+ "score": 0.8
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4841.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4841,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the fan and the sofa (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2.5",
+ "answer_given": "2.65",
+ "answer_raw": "2.65",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4842.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4842,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the table and the printer (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "4.3",
+ "answer_given": "0.0",
+ "answer_raw": "0.0",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4843.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4843,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the backpack and the printer (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "3.4",
+ "answer_given": "1.1",
+ "answer_raw": "1.1",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4844.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4844,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the door and the printer (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "3.0",
+ "answer_given": "1.71",
+ "answer_raw": "1.71",
+ "score": 0.2
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/4845.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 4845,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the table and the fan (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "3.4",
+ "answer_given": "3.65",
+ "answer_raw": "3.65",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/5033.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0593_00",
+ "dataset": "scannet",
+ "question_id": 5033,
+ "question_type": "route_planning",
+ "question": "You are a robot beginning at the sofa and facing the wall behind the sofa. You want to navigate to the printer. You will perform the following actions (Note: for each [please fill in], choose either 'turn back,' 'turn left,' or 'turn right.'): 1. [please fill in] 2. Go forward until the paper disposal bin. 3. [please fill in] 4. Go forward until the electric fan. 5. [please fill in] 6. Go forward until the printer. You have reached the final destination.",
+ "options": [
+  "A. Turn Right, Turn Right, Turn Right",
+  "B. Turn Left, Turn Left, Turn Left",
+  "C. Turn Left, Turn Right, Turn Left",
+  "D. Turn Back, Turn Right, Turn Right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "",
+ "answer_raw": "",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0593_00/_aggregate.json

@@ -0,0 +1,16 @@
+{
+ "scene_id": "scene0593_00",
+ "aggregate": {
+  "overall": 25.25974025974026,
+  "object_counting_MRA:.5:.95:.05": 10.0,
+  "object_abs_distance_MRA:.5:.95:.05": 45.714285714285715,
+  "object_size_estimation_MRA:.5:.95:.05": 51.66666666666667,
+  "room_size_estimation_MRA:.5:.95:.05": 0.0,
+  "object_rel_distance_accuracy": 36.36363636363637,
+  "object_rel_direction_accuracy": 0.0,
+  "route_planning_accuracy": 0.0,
+  "obj_appearance_order_accuracy": 58.333333333333336,
+  "tabulated_keys": "overall, object_counting_MRA:.5:.95:.05, object_abs_distance_MRA:.5:.95:.05, object_size_estimation_MRA:.5:.95:.05, room_size_estimation_MRA:.5:.95:.05, object_rel_distance_accuracy, object_rel_direction_accuracy, route_planning_accuracy, obj_appearance_order_accuracy",
+  "tabulated_results": "25.260, 10.000, 45.714, 51.667, 0.000, 36.364, 0.000, 0.000, 58.333"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3010.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3010,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (tv, sofa, table, backpack) is the closest to the chair?",
+ "options": [
+  "A. tv",
+  "B. sofa",
+  "C. table",
+  "D. backpack"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3011.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3011,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (door, backpack, tv, table) is the closest to the chair?",
+ "options": [
+  "A. door",
+  "B. backpack",
+  "C. tv",
+  "D. table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3012.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3012,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (sofa, chair, table, door) is the closest to the tv?",
+ "options": [
+  "A. sofa",
+  "B. chair",
+  "C. table",
+  "D. door"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3013.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3013,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (table, sofa, backpack, door) is the closest to the tv?",
+ "options": [
+  "A. table",
+  "B. sofa",
+  "C. backpack",
+  "D. door"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "A",
+ "answer_raw": "A",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3014.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3014,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (sofa, chair, backpack, table) is the closest to the tv?",
+ "options": [
+  "A. sofa",
+  "B. chair",
+  "C. backpack",
+  "D. table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3015.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3015,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (door, backpack, chair, sofa) is the closest to the tv?",
+ "options": [
+  "A. door",
+  "B. backpack",
+  "C. chair",
+  "D. sofa"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3016.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3016,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (door, table, chair, backpack) is the closest to the tv?",
+ "options": [
+  "A. door",
+  "B. table",
+  "C. chair",
+  "D. backpack"
+ ],
+ "full_prompt": null,
+ "answer_expected": "B",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3017.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3017,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (tv, door, chair, table) is the closest to the backpack?",
+ "options": [
+  "A. tv",
+  "B. door",
+  "C. chair",
+  "D. table"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3290.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3290,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the chair, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "89",
+ "answer_given": "67.0",
+ "answer_raw": "67.0",
+ "score": 0.6
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3291.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3291,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the tv, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "137",
+ "answer_given": "125.0",
+ "answer_raw": "125.0",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3292.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3292,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the backpack, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "44",
+ "answer_given": "37.0",
+ "answer_raw": "37.0",
+ "score": 0.7
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/3781.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 3781,
+ "question_type": "room_size_estimation",
+ "question": "What is the size of this room (in square meters)? \nIf multiple rooms are shown, estimate the size of the combined space.",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "31.1",
+ "answer_given": "16.8",
+ "answer_raw": "16.8",
+ "score": 0.1
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/4435.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 4435,
+ "question_type": "object_counting",
+ "question": "How many sofa(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2",
+ "answer_given": "1",
+ "answer_raw": "1",
+ "score": 0.1
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/4436.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 4436,
+ "question_type": "object_counting",
+ "question": "How many door(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "2",
+ "answer_given": "3",
+ "answer_raw": "3",
+ "score": 0.1
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/4437.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 4437,
+ "question_type": "object_counting",
+ "question": "How many table(s) are in this room?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "3",
+ "answer_given": "3",
+ "answer_raw": "3",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/4701.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 4701,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the tv and the chair (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "3.3",
+ "answer_given": "3.63",
+ "answer_raw": "3.63",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/4702.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 4702,
+ "question_type": "object_abs_distance",
+ "question": "Measuring from the closest point of each object, what is the distance between the backpack and the tv (in meters)?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "4.3",
+ "answer_given": "4.65",
+ "answer_raw": "4.65",
+ "score": 0.9
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/4988.json

@@ -0,0 +1,24 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0647_00",
+ "dataset": "scannet",
+ "question_id": 4988,
+ "question_type": "route_planning",
+ "question": "You are a robot beginning at the TV facing the drawing. You want to navigate to the table with two orange chair. You will perform the following actions (Note: for each [please fill in], choose either 'turn back,' 'turn left,' or 'turn right.'): 1. Go forward until the drawing 2. [please fill in] 3. Go forward until the desired chair. You have reached the final destination.",
+ "options": [
+  "A. Turn Back",
+  "B. Turn Left",
+  "C. Turn Right"
+ ],
+ "full_prompt": null,
+ "answer_expected": "C",
+ "answer_given": "",
+ "answer_raw": "",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0647_00/_aggregate.json

@@ -0,0 +1,14 @@
+{
+ "scene_id": "scene0647_00",
+ "aggregate": {
+  "overall": 50.138888888888886,
+  "object_counting_MRA:.5:.95:.05": 40.0,
+  "object_abs_distance_MRA:.5:.95:.05": 90.0,
+  "object_size_estimation_MRA:.5:.95:.05": 73.33333333333334,
+  "room_size_estimation_MRA:.5:.95:.05": 10.0,
+  "object_rel_distance_accuracy": 87.5,
+  "route_planning_accuracy": 0.0,
+  "tabulated_keys": "overall, object_counting_MRA:.5:.95:.05, object_abs_distance_MRA:.5:.95:.05, object_size_estimation_MRA:.5:.95:.05, room_size_estimation_MRA:.5:.95:.05, object_rel_distance_accuracy, route_planning_accuracy",
+  "tabulated_results": "50.139, 40.000, 90.000, 73.333, 10.000, 87.500, 0.000"
+ }
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3018.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3018,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (window, pillow, table, chair) is the closest to the bookshelf?",
+ "options": [
+  "A. window",
+  "B. pillow",
+  "C. table",
+  "D. chair"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "C",
+ "answer_raw": "C",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3019.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3019,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (plant, window, fan, backpack) is the closest to the closet?",
+ "options": [
+  "A. plant",
+  "B. window",
+  "C. fan",
+  "D. backpack"
+ ],
+ "full_prompt": null,
+ "answer_expected": "A",
+ "answer_given": "B",
+ "answer_raw": "B",
+ "score": 0.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3020.json

@@ -0,0 +1,25 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3020,
+ "question_type": "object_rel_distance",
+ "question": "Measuring from the closest point of each object, which of these objects (bookshelf, closet, plant, chair) is the closest to the fan?",
+ "options": [
+  "A. bookshelf",
+  "B. closet",
+  "C. plant",
+  "D. chair"
+ ],
+ "full_prompt": null,
+ "answer_expected": "D",
+ "answer_given": "D",
+ "answer_raw": "D",
+ "score": 1.0
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3293.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3293,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the window, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "137",
+ "answer_given": "102.0",
+ "answer_raw": "102.0",
+ "score": 0.5
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3294.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3294,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the bookshelf, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "114",
+ "answer_given": "88.0",
+ "answer_raw": "88.0",
+ "score": 0.6
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3295.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3295,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the lamp, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "53",
+ "answer_given": "32.0",
+ "answer_raw": "32.0",
+ "score": 0.3
+}

experiments/results/symbolic/metric/tracking/uniform/Select Representative Instances Using Track Persistence/32/scene0648_00/3296.json

@@ -0,0 +1,20 @@
+{
+ "model": "symbolic",
+ "condition": "metric:tracking:uniform:32",
+ "spatial_code_model": "sam3+depth-anything-3",
+ "depth": "metric",
+ "input": "uniform",
+ "tracking": "tracking",
+ "number_of_frames": 32,
+ "scene": "scene0648_00",
+ "dataset": "scannet",
+ "question_id": 3296,
+ "question_type": "object_size_estimation",
+ "question": "What is the length of the longest dimension (length, width, or height) of the closet, measured in centimeters?",
+ "options": null,
+ "full_prompt": null,
+ "answer_expected": "217",
+ "answer_given": "100.0",
+ "answer_raw": "100.0",
+ "score": 0.0
+}