Download data/leaderboard.json from VisionXLab/RISEBench_Leaderboard: direct link, hf CLI and curl.
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hf download hf://spaces/VisionXLab/RISEBench_Leaderboard/data/leaderboard.json
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curl -L -o leaderboard.json https://huggingface.co/spaces/VisionXLab/RISEBench_Leaderboard/resolve/main/data/leaderboard.json
435 kB
| { | |
| "schema_version": 3, | |
| "title": "RISE Leaderboard", | |
| "benchmarks": [ | |
| { | |
| "id": "risebench-plusplus", | |
| "name": "RISEBench++", | |
| "case_count": 1000, | |
| "available_result_languages": [ | |
| "en", | |
| "zh" | |
| ], | |
| "accuracy_unit": "%", | |
| "metric_unit": "/100", | |
| "score_decimals": 1, | |
| "default_sort": "total", | |
| "dimensions": [ | |
| { | |
| "key": "temporal", | |
| "label": "Temporal", | |
| "description": "Infer how a scene changes over time." | |
| }, | |
| { | |
| "key": "causal", | |
| "label": "Causal", | |
| "description": "Reason about causes, actions, and their consequences." | |
| }, | |
| { | |
| "key": "spatial", | |
| "label": "Spatial", | |
| "description": "Reason about spatial relationships and transformations." | |
| }, | |
| { | |
| "key": "logical", | |
| "label": "Logical", | |
| "description": "Apply explicit rules, patterns, and logical constraints." | |
| }, | |
| { | |
| "key": "counterfactual", | |
| "label": "Counterfactual", | |
| "description": "Visualize outcomes under hypothetical or contrary-to-fact conditions." | |
| }, | |
| { | |
| "key": "hybrid", | |
| "label": "Hybrid", | |
| "description": "Combine reasoning across three to five successive editing instructions." | |
| } | |
| ], | |
| "metrics": [ | |
| { | |
| "key": "instruction_reasoning", | |
| "label": "Instruction Reasoning", | |
| "description": "Whether the edit realizes the intended reasoning outcome." | |
| }, | |
| { | |
| "key": "appearance_consistency", | |
| "label": "Appearance Consistency", | |
| "description": "Whether content that should remain unchanged is preserved." | |
| }, | |
| { | |
| "key": "visual_plausibility", | |
| "label": "Visual Plausibility", | |
| "description": "Visual quality and plausibility; logical tasks are excluded." | |
| } | |
| ], | |
| "accuracy_columns": [ | |
| { | |
| "key": "temporal", | |
| "label": "Temporal", | |
| "description": "Infer how a scene changes over time." | |
| }, | |
| { | |
| "key": "causal", | |
| "label": "Causal", | |
| "description": "Reason about causes, actions, and their consequences." | |
| }, | |
| { | |
| "key": "spatial", | |
| "label": "Spatial", | |
| "description": "Reason about spatial relationships and transformations." | |
| }, | |
| { | |
| "key": "logical", | |
| "label": "Logical", | |
| "description": "Apply explicit rules, patterns, and logical constraints." | |
| }, | |
| { | |
| "key": "counterfactual", | |
| "label": "Counterfactual", | |
| "description": "Visualize outcomes under hypothetical or contrary-to-fact conditions." | |
| }, | |
| { | |
| "key": "hybrid", | |
| "label": "Hybrid", | |
| "description": "Combine reasoning across three to five successive editing instructions." | |
| }, | |
| { | |
| "key": "single", | |
| "label": "Single", | |
| "description": "Accuracy on single-image cases." | |
| }, | |
| { | |
| "key": "multi", | |
| "label": "Multi", | |
| "description": "Accuracy on multi-image cases. Not evaluated for models without multi-image support." | |
| }, | |
| { | |
| "key": "total", | |
| "label": "Total", | |
| "description": "Accuracy on the complete benchmark. Not evaluated for single-image-only models." | |
| } | |
| ], | |
| "subcategory_columns": [ | |
| { | |
| "key": "temporal_common_sense_knowledge", | |
| "label": "Common-Sense Knowledge", | |
| "dimension": "temporal", | |
| "case_count": 85, | |
| "multi_image_case_count": 0, | |
| "code": "CSK", | |
| "description": "Temporal · Common-Sense Knowledge — accuracy (%)" | |
| }, | |
| { | |
| "key": "temporal_context_knowledge", | |
| "label": "Context Knowledge", | |
| "dimension": "temporal", | |
| "case_count": 52, | |
| "multi_image_case_count": 28, | |
| "code": "CtxK", | |
| "description": "Temporal · Context Knowledge — accuracy (%)" | |
| }, | |
| { | |
| "key": "temporal_disciplinary_knowledge", | |
| "label": "Disciplinary Knowledge", | |
| "dimension": "temporal", | |
| "case_count": 63, | |
| "multi_image_case_count": 4, | |
| "code": "DK", | |
| "description": "Temporal · Disciplinary Knowledge — accuracy (%)" | |
| }, | |
| { | |
| "key": "causal_common_sense_knowledge", | |
| "label": "Common-Sense Knowledge", | |
| "dimension": "causal", | |
| "case_count": 80, | |
| "multi_image_case_count": 1, | |
| "code": "CSK", | |
| "description": "Causal · Common-Sense Knowledge — accuracy (%)" | |
| }, | |
| { | |
| "key": "causal_context_knowledge", | |
| "label": "Context Knowledge", | |
| "dimension": "causal", | |
| "case_count": 40, | |
| "multi_image_case_count": 2, | |
| "code": "CtxK", | |
| "description": "Causal · Context Knowledge — accuracy (%)" | |
| }, | |
| { | |
| "key": "causal_disciplinary_knowledge", | |
| "label": "Disciplinary Knowledge", | |
| "dimension": "causal", | |
| "case_count": 80, | |
| "multi_image_case_count": 5, | |
| "code": "DK", | |
| "description": "Causal · Disciplinary Knowledge — accuracy (%)" | |
| }, | |
| { | |
| "key": "spatial_relation", | |
| "label": "Relation", | |
| "dimension": "spatial", | |
| "case_count": 106, | |
| "multi_image_case_count": 6, | |
| "code": "Rel.", | |
| "description": "Spatial · Relation — accuracy (%)" | |
| }, | |
| { | |
| "key": "spatial_structure", | |
| "label": "Structure", | |
| "dimension": "spatial", | |
| "case_count": 94, | |
| "multi_image_case_count": 12, | |
| "code": "Struct.", | |
| "description": "Spatial · Structure — accuracy (%)" | |
| }, | |
| { | |
| "key": "logical_explicit_rule_deduction", | |
| "label": "Explicit Rule Deduction", | |
| "dimension": "logical", | |
| "case_count": 123, | |
| "multi_image_case_count": 0, | |
| "code": "ERD", | |
| "description": "Logical · Explicit Rule Deduction — accuracy (%)" | |
| }, | |
| { | |
| "key": "logical_implicit_pattern_induction", | |
| "label": "Implicit Pattern Induction", | |
| "dimension": "logical", | |
| "case_count": 77, | |
| "multi_image_case_count": 20, | |
| "code": "IPI", | |
| "description": "Logical · Implicit Pattern Induction — accuracy (%)" | |
| }, | |
| { | |
| "key": "counterfactual_counterfactual_imagination", | |
| "label": "Counterfactual Imagination", | |
| "dimension": "counterfactual", | |
| "case_count": 70, | |
| "multi_image_case_count": 0, | |
| "code": "CFI", | |
| "description": "Counterfactual · Counterfactual Imagination — accuracy (%)" | |
| }, | |
| { | |
| "key": "counterfactual_anomaly_correction_and_generation", | |
| "label": "Anomaly Correction and Generation", | |
| "dimension": "counterfactual", | |
| "case_count": 30, | |
| "multi_image_case_count": 0, | |
| "code": "ACG", | |
| "description": "Counterfactual · Anomaly Correction and Generation — accuracy (%)" | |
| } | |
| ], | |
| "task_type_columns": [ | |
| { | |
| "key": "T01", | |
| "code": "T01", | |
| "label": "Life Progression", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 24, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Life Progression — accuracy (%)" | |
| }, | |
| { | |
| "key": "T02", | |
| "code": "T02", | |
| "label": "Material Transformation", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 9, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Material Transformation — accuracy (%)" | |
| }, | |
| { | |
| "key": "T03", | |
| "code": "T03", | |
| "label": "Natural Environmental Changes", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 13, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Natural Environmental Changes — accuracy (%)" | |
| }, | |
| { | |
| "key": "T04", | |
| "code": "T04", | |
| "label": "Physical Aging", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 20, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Physical Aging — accuracy (%)" | |
| }, | |
| { | |
| "key": "T05", | |
| "code": "T05", | |
| "label": "Social Activities", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 8, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Social Activities — accuracy (%)" | |
| }, | |
| { | |
| "key": "T06", | |
| "code": "T06", | |
| "label": "Tool Evolution", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 7, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Tool Evolution — accuracy (%)" | |
| }, | |
| { | |
| "key": "T07", | |
| "code": "T07", | |
| "label": "Urban Evolution", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_common_sense_knowledge", | |
| "case_count": 4, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Urban Evolution — accuracy (%)" | |
| }, | |
| { | |
| "key": "T08", | |
| "code": "T08", | |
| "label": "Temporal State Transition", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_context_knowledge", | |
| "case_count": 15, | |
| "multi_image_case_count": 4, | |
| "description": "Temporal · Temporal State Transition — accuracy (%)" | |
| }, | |
| { | |
| "key": "T09", | |
| "code": "T09", | |
| "label": "Precise Temporal Localization", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_context_knowledge", | |
| "case_count": 14, | |
| "multi_image_case_count": 2, | |
| "description": "Temporal · Precise Temporal Localization — accuracy (%)" | |
| }, | |
| { | |
| "key": "T10", | |
| "code": "T10", | |
| "label": "Position Change", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_context_knowledge", | |
| "case_count": 15, | |
| "multi_image_case_count": 14, | |
| "description": "Temporal · Position Change — accuracy (%)" | |
| }, | |
| { | |
| "key": "T11", | |
| "code": "T11", | |
| "label": "Action Sequence", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_context_knowledge", | |
| "case_count": 8, | |
| "multi_image_case_count": 8, | |
| "description": "Temporal · Action Sequence — accuracy (%)" | |
| }, | |
| { | |
| "key": "T12", | |
| "code": "T12", | |
| "label": "Physics", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 4, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Physics — accuracy (%)" | |
| }, | |
| { | |
| "key": "T13", | |
| "code": "T13", | |
| "label": "Chemistry", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 8, | |
| "multi_image_case_count": 4, | |
| "description": "Temporal · Chemistry — accuracy (%)" | |
| }, | |
| { | |
| "key": "T14", | |
| "code": "T14", | |
| "label": "Biology", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 9, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Biology — accuracy (%)" | |
| }, | |
| { | |
| "key": "T15", | |
| "code": "T15", | |
| "label": "Astronomy", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 12, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Astronomy — accuracy (%)" | |
| }, | |
| { | |
| "key": "T16", | |
| "code": "T16", | |
| "label": "Geography", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 18, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Geography — accuracy (%)" | |
| }, | |
| { | |
| "key": "T17", | |
| "code": "T17", | |
| "label": "History", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 5, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · History — accuracy (%)" | |
| }, | |
| { | |
| "key": "T18", | |
| "code": "T18", | |
| "label": "Medicine", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 4, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Medicine — accuracy (%)" | |
| }, | |
| { | |
| "key": "T19", | |
| "code": "T19", | |
| "label": "Computer Science", | |
| "dimension": "temporal", | |
| "subcategory": "temporal_disciplinary_knowledge", | |
| "case_count": 3, | |
| "multi_image_case_count": 0, | |
| "description": "Temporal · Computer Science — accuracy (%)" | |
| }, | |
| { | |
| "key": "C01", | |
| "code": "C01", | |
| "label": "Physical State Transition", | |
| "dimension": "causal", | |
| "subcategory": "causal_common_sense_knowledge", | |
| "case_count": 31, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Physical State Transition — accuracy (%)" | |
| }, | |
| { | |
| "key": "C02", | |
| "code": "C02", | |
| "label": "Structural Damage", | |
| "dimension": "causal", | |
| "subcategory": "causal_common_sense_knowledge", | |
| "case_count": 27, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Structural Damage — accuracy (%)" | |
| }, | |
| { | |
| "key": "C03", | |
| "code": "C03", | |
| "label": "Flexible Deformation", | |
| "dimension": "causal", | |
| "subcategory": "causal_common_sense_knowledge", | |
| "case_count": 22, | |
| "multi_image_case_count": 1, | |
| "description": "Causal · Flexible Deformation — accuracy (%)" | |
| }, | |
| { | |
| "key": "C04", | |
| "code": "C04", | |
| "label": "Magnitude Change", | |
| "dimension": "causal", | |
| "subcategory": "causal_context_knowledge", | |
| "case_count": 10, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Magnitude Change — accuracy (%)" | |
| }, | |
| { | |
| "key": "C05", | |
| "code": "C05", | |
| "label": "Reading Offset", | |
| "dimension": "causal", | |
| "subcategory": "causal_context_knowledge", | |
| "case_count": 10, | |
| "multi_image_case_count": 2, | |
| "description": "Causal · Reading Offset — accuracy (%)" | |
| }, | |
| { | |
| "key": "C06", | |
| "code": "C06", | |
| "label": "Order Relation", | |
| "dimension": "causal", | |
| "subcategory": "causal_context_knowledge", | |
| "case_count": 10, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Order Relation — accuracy (%)" | |
| }, | |
| { | |
| "key": "C07", | |
| "code": "C07", | |
| "label": "Feature Mapping", | |
| "dimension": "causal", | |
| "subcategory": "causal_context_knowledge", | |
| "case_count": 10, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Feature Mapping — accuracy (%)" | |
| }, | |
| { | |
| "key": "C08", | |
| "code": "C08", | |
| "label": "Physics", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 25, | |
| "multi_image_case_count": 1, | |
| "description": "Causal · Physics — accuracy (%)" | |
| }, | |
| { | |
| "key": "C09", | |
| "code": "C09", | |
| "label": "Chemistry", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 23, | |
| "multi_image_case_count": 4, | |
| "description": "Causal · Chemistry — accuracy (%)" | |
| }, | |
| { | |
| "key": "C10", | |
| "code": "C10", | |
| "label": "Biology", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 12, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Biology — accuracy (%)" | |
| }, | |
| { | |
| "key": "C11", | |
| "code": "C11", | |
| "label": "Astronomy", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 3, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Astronomy — accuracy (%)" | |
| }, | |
| { | |
| "key": "C12", | |
| "code": "C12", | |
| "label": "Medicine", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 4, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Medicine — accuracy (%)" | |
| }, | |
| { | |
| "key": "C13", | |
| "code": "C13", | |
| "label": "Music Theory", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 3, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Music Theory — accuracy (%)" | |
| }, | |
| { | |
| "key": "C14", | |
| "code": "C14", | |
| "label": "Computer Science", | |
| "dimension": "causal", | |
| "subcategory": "causal_disciplinary_knowledge", | |
| "case_count": 10, | |
| "multi_image_case_count": 0, | |
| "description": "Causal · Computer Science — accuracy (%)" | |
| }, | |
| { | |
| "key": "S01", | |
| "code": "S01", | |
| "label": "Adjacency", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 11, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Adjacency — accuracy (%)" | |
| }, | |
| { | |
| "key": "S02", | |
| "code": "S02", | |
| "label": "Direction", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 11, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Direction — accuracy (%)" | |
| }, | |
| { | |
| "key": "S03", | |
| "code": "S03", | |
| "label": "Orientation", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 11, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Orientation — accuracy (%)" | |
| }, | |
| { | |
| "key": "S04", | |
| "code": "S04", | |
| "label": "Projection", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 12, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Projection — accuracy (%)" | |
| }, | |
| { | |
| "key": "S05", | |
| "code": "S05", | |
| "label": "Distance", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 13, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Distance — accuracy (%)" | |
| }, | |
| { | |
| "key": "S06", | |
| "code": "S06", | |
| "label": "Size", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 15, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Size — accuracy (%)" | |
| }, | |
| { | |
| "key": "S07", | |
| "code": "S07", | |
| "label": "Configuration", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 18, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Configuration — accuracy (%)" | |
| }, | |
| { | |
| "key": "S08", | |
| "code": "S08", | |
| "label": "Viewing Scale", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 9, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Viewing Scale — accuracy (%)" | |
| }, | |
| { | |
| "key": "S09", | |
| "code": "S09", | |
| "label": "Localization", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_relation", | |
| "case_count": 6, | |
| "multi_image_case_count": 6, | |
| "description": "Spatial · Localization — accuracy (%)" | |
| }, | |
| { | |
| "key": "S10", | |
| "code": "S10", | |
| "label": "Part-Whole Perception", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_structure", | |
| "case_count": 24, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Part-Whole Perception — accuracy (%)" | |
| }, | |
| { | |
| "key": "S11", | |
| "code": "S11", | |
| "label": "Geometric Regularities Reasoning", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_structure", | |
| "case_count": 15, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Geometric Regularities Reasoning — accuracy (%)" | |
| }, | |
| { | |
| "key": "S12", | |
| "code": "S12", | |
| "label": "Viewpoint Generation", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_structure", | |
| "case_count": 26, | |
| "multi_image_case_count": 0, | |
| "description": "Spatial · Viewpoint Generation — accuracy (%)" | |
| }, | |
| { | |
| "key": "S13", | |
| "code": "S13", | |
| "label": "Environmental Structure Reasoning", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_structure", | |
| "case_count": 19, | |
| "multi_image_case_count": 2, | |
| "description": "Spatial · Environmental Structure Reasoning — accuracy (%)" | |
| }, | |
| { | |
| "key": "S14", | |
| "code": "S14", | |
| "label": "Egocentric Scene Reconstruction", | |
| "dimension": "spatial", | |
| "subcategory": "spatial_structure", | |
| "case_count": 10, | |
| "multi_image_case_count": 10, | |
| "description": "Spatial · Egocentric Scene Reconstruction — accuracy (%)" | |
| }, | |
| { | |
| "key": "L01", | |
| "code": "L01", | |
| "label": "Path Searching", | |
| "dimension": "logical", | |
| "subcategory": "logical_explicit_rule_deduction", | |
| "case_count": 24, | |
| "multi_image_case_count": 0, | |
| "description": "Logical · Path Searching — accuracy (%)" | |
| }, | |
| { | |
| "key": "L02", | |
| "code": "L02", | |
| "label": "Mathematical Derivation", | |
| "dimension": "logical", | |
| "subcategory": "logical_explicit_rule_deduction", | |
| "case_count": 27, | |
| "multi_image_case_count": 0, | |
| "description": "Logical · Mathematical Derivation — accuracy (%)" | |
| }, | |
| { | |
| "key": "L03", | |
| "code": "L03", | |
| "label": "Game Deduction", | |
| "dimension": "logical", | |
| "subcategory": "logical_explicit_rule_deduction", | |
| "case_count": 37, | |
| "multi_image_case_count": 0, | |
| "description": "Logical · Game Deduction — accuracy (%)" | |
| }, | |
| { | |
| "key": "L04", | |
| "code": "L04", | |
| "label": "Puzzle Solving", | |
| "dimension": "logical", | |
| "subcategory": "logical_explicit_rule_deduction", | |
| "case_count": 35, | |
| "multi_image_case_count": 0, | |
| "description": "Logical · Puzzle Solving — accuracy (%)" | |
| }, | |
| { | |
| "key": "L05", | |
| "code": "L05", | |
| "label": "Pattern Prediction", | |
| "dimension": "logical", | |
| "subcategory": "logical_implicit_pattern_induction", | |
| "case_count": 39, | |
| "multi_image_case_count": 0, | |
| "description": "Logical · Pattern Prediction — accuracy (%)" | |
| }, | |
| { | |
| "key": "L06", | |
| "code": "L06", | |
| "label": "Visual Oddity Detection", | |
| "dimension": "logical", | |
| "subcategory": "logical_implicit_pattern_induction", | |
| "case_count": 18, | |
| "multi_image_case_count": 0, | |
| "description": "Logical · Visual Oddity Detection — accuracy (%)" | |
| }, | |
| { | |
| "key": "L07", | |
| "code": "L07", | |
| "label": "Rule Transfer", | |
| "dimension": "logical", | |
| "subcategory": "logical_implicit_pattern_induction", | |
| "case_count": 20, | |
| "multi_image_case_count": 20, | |
| "description": "Logical · Rule Transfer — accuracy (%)" | |
| }, | |
| { | |
| "key": "F01", | |
| "code": "F01", | |
| "label": "Physical Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 23, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Physical Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F02", | |
| "code": "F02", | |
| "label": "Chemical Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 9, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Chemical Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F03", | |
| "code": "F03", | |
| "label": "Biological Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 8, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Biological Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F04", | |
| "code": "F04", | |
| "label": "Astronomy Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 7, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Astronomy Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F05", | |
| "code": "F05", | |
| "label": "Geography Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 8, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Geography Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F06", | |
| "code": "F06", | |
| "label": "History Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 7, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · History Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F07", | |
| "code": "F07", | |
| "label": "Music Theory Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 4, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Music Theory Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F08", | |
| "code": "F08", | |
| "label": "Computer Science Counterfactual", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_counterfactual_imagination", | |
| "case_count": 4, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Computer Science Counterfactual — accuracy (%)" | |
| }, | |
| { | |
| "key": "F09", | |
| "code": "F09", | |
| "label": "Anatomical Errors", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_anomaly_correction_and_generation", | |
| "case_count": 10, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Anatomical Errors — accuracy (%)" | |
| }, | |
| { | |
| "key": "F10", | |
| "code": "F10", | |
| "label": "Structural Anomalies", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_anomaly_correction_and_generation", | |
| "case_count": 11, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Structural Anomalies — accuracy (%)" | |
| }, | |
| { | |
| "key": "F11", | |
| "code": "F11", | |
| "label": "Relational Anomalies", | |
| "dimension": "counterfactual", | |
| "subcategory": "counterfactual_anomaly_correction_and_generation", | |
| "case_count": 9, | |
| "multi_image_case_count": 0, | |
| "description": "Counterfactual · Relational Anomalies — accuracy (%)" | |
| } | |
| ], | |
| "links": { | |
| "paper": "https://arxiv.org/abs/2610.12343", | |
| "data": "https://huggingface.co/datasets/VisionXLab/RISEBench-plusplus", | |
| "outputs": "https://huggingface.co/datasets/VisionXLab/RISEBench-plusplus_Outputs", | |
| "github": "https://github.com/VisionXLab/RISEBench/tree/main/RISEBench%2B%2B" | |
| }, | |
| "judges": { | |
| "instruction_reasoning": "Gemini-3-Flash", | |
| "appearance_consistency": "Gemini-3-Flash", | |
| "visual_plausibility": "Gemini-3.1-Flash-Lite" | |
| }, | |
| "results_by_language": { | |
| "en": { | |
| "language": "English", | |
| "language_code": "en", | |
| "model_count": 58, | |
| "groups": [ | |
| { | |
| "id": "closed", | |
| "label": "Closed-source Models", | |
| "count": 19 | |
| }, | |
| { | |
| "id": "open", | |
| "label": "Open-source Models", | |
| "count": 34 | |
| }, | |
| { | |
| "id": "agentic", | |
| "label": "Agentic Methods", | |
| "count": 5 | |
| } | |
| ], | |
| "models": [ | |
| { | |
| "id": "gpt-image-2-5-sunburst", | |
| "name": "GPT-Image-2.5 Sunburst", | |
| "group": "closed", | |
| "multi_image": true, | |
| "source_order": 1, | |
| "accuracy": { | |
| "temporal": 67.5, | |
| "causal": 69.0, | |
| "spatial": 64.0, | |
| "logical": 27.0, | |
| "counterfactual": 72.0, | |
| "hybrid": 39.0, | |
| "single": 56.9, | |
| "multi": 52.6, | |
| "total": 56.6 | |
| }, | |
| "metrics": { | |
| "instruction_reasoning": 68.1, | |
| "appearance_consistency": 96.3, | |
| "visual_plausibility": 98.0 | |
| }, | |
| "subcategories": { | |
| "temporal_common_sense_knowledge": 72.9, | |
| "temporal_context_knowledge": 67.3, | |
| "temporal_disciplinary_knowledge": 60.3, | |
| "causal_common_sense_knowledge": 78.8, | |
| "causal_context_knowledge": 55.0, | |
| "causal_disciplinary_knowledge": 66.3, | |
| "spatial_relation": 63.2, | |
| "spatial_structure": 64.9, | |
| "logical_explicit_rule_deduction": 32.5, | |
| "logical_implicit_pattern_induction": 18.2, | |
| "counterfactual_counterfactual_imagination": 71.4, | |
| "counterfactual_anomaly_correction_and_generation": 73.3 | |
| }, | |
| "task_types": { | |
| "T01": 58.3, | |
| "T02": 88.9, | |
| "T03": 76.9, | |
| "T04": 80.0, | |
| "T05": 87.5, | |
| "T06": 71.4, | |
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| "T09": 50.0, | |
| "T10": 73.3, | |
| "T11": 100.0, | |
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| "T13": 50.0, | |
| "T14": 66.7, | |
| "T15": 58.3, | |
| "T16": 66.7, | |
| "T17": 40.0, | |
| "T18": 75.0, | |
| "T19": 66.7, | |
| "C01": 80.6, | |
| "C02": 85.2, | |
| "C03": 68.2, | |
| "C04": 50.0, | |
| "C05": 60.0, | |
| "C06": 30.0, | |
| "C07": 80.0, | |
| "C08": 56.0, | |
| "C09": 69.6, | |
| "C10": 100.0, | |
| "C11": 100.0, | |
| "C12": 50.0, | |
| "C13": 66.7, | |
| "C14": 40.0, | |
| "S01": 63.6, | |
| "S02": 72.7, | |
| "S03": 45.5, | |
| "S04": 58.3, | |
| "S05": 76.9, | |
| "S06": 80.0, | |
| "S07": 72.2, | |
| "S08": 44.4, | |
| "S09": 16.7, | |
| "S10": 79.2, | |
| "S11": 73.3, | |
| "S12": 65.4, | |
| "S13": 52.6, | |
| "S14": 40.0, | |
| "L01": 25.0, | |
| "L02": 29.6, | |
| "L03": 40.5, | |
| "L04": 31.4, | |
| "L05": 12.8, | |
| "L06": 33.3, | |
| "L07": 15.0, | |
| "F01": 87.0, | |
| "F02": 66.7, | |
| "F03": 87.5, | |
| "F04": 42.9, | |
| "F05": 75.0, | |
| "F06": 57.1, | |
| "F07": 50.0, | |
| "F08": 50.0, | |
| "F09": 90.0, | |
| "F10": 63.6, | |
| "F11": 66.7 | |
| } | |
| }, | |
| { | |
| "id": "nano-banana-pro", | |
| "name": "Nano Banana Pro", | |
| "group": "closed", | |
| "multi_image": true, | |
| "source_order": 2, | |
| "accuracy": { | |
| "temporal": 63.0, | |
| "causal": 71.0, | |
| "spatial": 51.5, | |
| "logical": 36.0, | |
| "counterfactual": 65.0, | |
| "hybrid": 38.0, | |
| "single": 55.4, | |
| "multi": 44.9, | |
| "total": 54.6 | |
| }, | |
| "metrics": { | |
| "instruction_reasoning": 69.8, | |
| "appearance_consistency": 87.7, | |
| "visual_plausibility": 96.8 | |
| }, | |
| "subcategories": { | |
| "temporal_common_sense_knowledge": 68.2, | |
| "temporal_context_knowledge": 63.5, | |
| "temporal_disciplinary_knowledge": 55.6, | |
| "causal_common_sense_knowledge": 77.5, | |
| "causal_context_knowledge": 65.0, | |
| "causal_disciplinary_knowledge": 67.5, | |
| "spatial_relation": 50.9, | |
| "spatial_structure": 52.1, | |
| "logical_explicit_rule_deduction": 41.5, | |
| "logical_implicit_pattern_induction": 27.3, | |
| "counterfactual_counterfactual_imagination": 61.4, | |
| "counterfactual_anomaly_correction_and_generation": 73.3 | |
| }, | |
| "task_types": { | |
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| "T02": 100.0, | |
| "T03": 76.9, | |
| "T04": 70.0, | |
| "T05": 50.0, | |
| "T06": 42.9, | |
| "T07": 75.0, | |
| "T08": 66.7, | |
| "T09": 64.3, | |
| "T10": 60.0, | |
| "T11": 62.5, | |
| "T12": 75.0, | |
| "T13": 25.0, | |
| "T14": 66.7, | |
| "T15": 66.7, | |
| "T16": 50.0, | |
| "T17": 60.0, | |
| "T18": 75.0, | |
| "T19": 33.3, | |
| "C01": 74.2, | |
| "C02": 74.1, | |
| "C03": 86.4, | |
| "C04": 40.0, | |
| "C05": 80.0, | |
| "C06": 60.0, | |
| "C07": 80.0, | |
| "C08": 64.0, | |
| "C09": 73.9, | |
| "C10": 91.7, | |
| "C11": 100.0, | |
| "C12": 50.0, | |
| "C13": 33.3, | |
| "C14": 40.0, | |
| "S01": 81.8, | |
| "S02": 45.5, | |
| "S03": 54.5, | |
| "S04": 58.3, | |
| "S05": 53.8, | |
| "S06": 46.7, | |
| "S07": 55.6, | |
| "S08": 33.3, | |
| "S09": 0.0, | |
| "S10": 58.3, | |
| "S11": 66.7, | |
| "S12": 50.0, | |
| "S13": 36.8, | |
| "S14": 50.0, | |
| "L01": 29.2, | |
| "L02": 66.7, | |
| "L03": 45.9, | |
| "L04": 25.7, | |
| "L05": 25.6, | |
| "L06": 27.8, | |
| "L07": 30.0, | |
| "F01": 78.3, | |
| "F02": 55.6, | |
| "F03": 87.5, | |
| "F04": 42.9, | |
| "F05": 12.5, | |
| "F06": 85.7, | |
| "F07": 25.0, | |
| "F08": 50.0, | |
| "F09": 80.0, | |
| "F10": 81.8, | |
| "F11": 55.6 | |
| } | |
| }, | |
| { | |
| "id": "nano-banana-2", | |
| "name": "Nano Banana 2", | |
| "group": "closed", | |
| "multi_image": true, | |
| "source_order": 3, | |
| "accuracy": { | |
| "temporal": 67.5, | |
| "causal": 67.0, | |
| "spatial": 45.0, | |
| "logical": 28.5, | |
| "counterfactual": 62.0, | |
| "hybrid": 30.0, | |
| "single": 51.3, | |
| "multi": 44.9, | |
| "total": 50.8 | |
| }, | |
| "metrics": { | |
| "instruction_reasoning": 68.5, | |
| "appearance_consistency": 91.1, | |
| "visual_plausibility": 97.2 | |
| }, | |
| "subcategories": { | |
| "temporal_common_sense_knowledge": 77.6, | |
| "temporal_context_knowledge": 63.5, | |
| "temporal_disciplinary_knowledge": 57.1, | |
| "causal_common_sense_knowledge": 76.3, | |
| "causal_context_knowledge": 50.0, | |
| "causal_disciplinary_knowledge": 66.3, | |
| "spatial_relation": 47.2, | |
| "spatial_structure": 42.6, | |
| "logical_explicit_rule_deduction": 38.2, | |
| "logical_implicit_pattern_induction": 13.0, | |
| "counterfactual_counterfactual_imagination": 58.6, | |
| "counterfactual_anomaly_correction_and_generation": 70.0 | |
| }, | |
| "task_types": { | |
| "T01": 62.5, | |
| "T02": 88.9, | |
| "T03": 76.9, | |
| "T04": 90.0, | |
| "T05": 100.0, | |
| "T06": 57.1, | |
| "T07": 75.0, | |
| "T08": 60.0, | |
| "T09": 71.4, | |
| "T10": 53.3, | |
| "T11": 75.0, | |
| "T12": 25.0, | |
| "T13": 37.5, | |
| "T14": 55.6, | |
| "T15": 66.7, | |
| "T16": 55.6, | |
| "T17": 100.0, | |
| "T18": 50.0, | |
| "T19": 66.7, | |
| "C01": 71.0, | |
| "C02": 74.1, | |
| "C03": 86.4, | |
| "C04": 40.0, | |
| "C05": 40.0, | |
| "C06": 70.0, | |
| "C07": 50.0, | |
| "C08": 64.0, | |
| "C09": 73.9, | |
| "C10": 91.7, | |
| "C11": 66.7, | |
| "C12": 50.0, | |
| "C13": 0.0, | |
| "C14": 50.0, | |
| "S01": 54.5, | |
| "S02": 54.5, | |
| "S03": 36.4, | |
| "S04": 41.7, | |
| "S05": 46.2, | |
| "S06": 60.0, | |
| "S07": 55.6, | |
| "S08": 33.3, | |
| "S09": 16.7, | |
| "S10": 41.7, | |
| "S11": 53.3, | |
| "S12": 34.6, | |
| "S13": 42.1, | |
| "S14": 50.0, | |
| "L01": 33.3, | |
| "L02": 51.9, | |
| "L03": 45.9, | |
| "L04": 22.9, | |
| "L05": 12.8, | |
| "L06": 27.8, | |
| "L07": 0.0, | |
| "F01": 65.2, | |
| "F02": 55.6, | |
| "F03": 100.0, | |
| "F04": 28.6, | |
| "F05": 12.5, | |
| "F06": 71.4, | |
| "F07": 50.0, | |
| "F08": 75.0, | |
| "F09": 80.0, | |
| "F10": 81.8, | |
| "F11": 44.4 | |
| } | |
| }, | |
| { | |
| "id": "gpt-image-2", | |
| "name": "GPT-Image-2", | |
| "group": "closed", | |
| "multi_image": true, | |
| "source_order": 4, | |
| "accuracy": { | |
| "temporal": 59.5, | |
| "causal": 64.5, | |
| "spatial": 60.5, | |
| "logical": 15.0, | |
| "counterfactual": 58.0, | |
| "hybrid": 21.0, | |
| "single": 48.2, | |
| "multi": 43.6, | |
| "total": 47.8 | |
| }, | |
| "metrics": { | |
| "instruction_reasoning": 61.5, | |
| "appearance_consistency": 95.2, | |
| "visual_plausibility": 97.6 | |
| }, | |
| "subcategories": { | |
| "temporal_common_sense_knowledge": 61.2, | |
| "temporal_context_knowledge": 67.3, | |
| "temporal_disciplinary_knowledge": 50.8, | |
| "causal_common_sense_knowledge": 76.3, | |
| "causal_context_knowledge": 60.0, | |
| "causal_disciplinary_knowledge": 55.0, | |
| "spatial_relation": 60.4, | |
| "spatial_structure": 60.6, | |
| "logical_explicit_rule_deduction": 21.1, | |
| "logical_implicit_pattern_induction": 5.2, | |
| "counterfactual_counterfactual_imagination": 52.9, | |
| "counterfactual_anomaly_correction_and_generation": 70.0 | |
| }, | |
| "task_types": { | |
| "T01": 58.3, | |
| "T02": 88.9, | |
| "T03": 69.2, | |
| "T04": 65.0, | |
| "T05": 62.5, | |
| "T06": 42.9, | |
| "T07": 0.0, | |
| "T08": 53.3, | |
| "T09": 64.3, | |
| "T10": 86.7, | |
| "T11": 62.5, | |
| "T12": 50.0, | |
| "T13": 50.0, | |
| "T14": 66.7, | |
| "T15": 50.0, | |
| "T16": 44.4, | |
| "T17": 40.0, | |
| "T18": 75.0, | |
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| } | |
| ] | |
| } | |
| } | |
| }, | |
| { | |
| "id": "risebench", | |
| "name": "RISEBench", | |
| "case_count": 360, | |
| "available_result_languages": [ | |
| "en" | |
| ], | |
| "accuracy_unit": "%", | |
| "metric_unit": "/100", | |
| "score_decimals": 1, | |
| "default_sort": "total", | |
| "dimensions": [ | |
| { | |
| "key": "temporal", | |
| "label": "Temporal", | |
| "description": "Infer how a scene changes over time." | |
| }, | |
| { | |
| "key": "causal", | |
| "label": "Causal", | |
| "description": "Reason about causes, actions, and their consequences." | |
| }, | |
| { | |
| "key": "spatial", | |
| "label": "Spatial", | |
| "description": "Reason about spatial relationships and transformations." | |
| }, | |
| { | |
| "key": "logical", | |
| "label": "Logical", | |
| "description": "Apply explicit rules, patterns, and logical constraints." | |
| } | |
| ], | |
| "metrics": [ | |
| { | |
| "key": "instruction_reasoning", | |
| "label": "Instruction Reasoning", | |
| "description": "Whether the edit realizes the intended reasoning outcome." | |
| }, | |
| { | |
| "key": "appearance_consistency", | |
| "label": "Appearance Consistency", | |
| "description": "Whether content that should remain unchanged is preserved." | |
| }, | |
| { | |
| "key": "visual_plausibility", | |
| "label": "Visual Plausibility", | |
| "description": "Visual quality and plausibility; logical tasks are excluded." | |
| } | |
| ], | |
| "accuracy_columns": [ | |
| { | |
| "key": "temporal", | |
| "label": "Temporal", | |
| "description": "Infer how a scene changes over time." | |
| }, | |
| { | |
| "key": "causal", | |
| "label": "Causal", | |
| "description": "Reason about causes, actions, and their consequences." | |
| }, | |
| { | |
| "key": "spatial", | |
| "label": "Spatial", | |
| "description": "Reason about spatial relationships and transformations." | |
| }, | |
| { | |
| "key": "logical", | |
| "label": "Logical", | |
| "description": "Apply explicit rules, patterns, and logical constraints." | |
| }, | |
| { | |
| "key": "total", | |
| "label": "Overall", | |
| "description": "Accuracy on the complete RISEBench-360 benchmark." | |
| } | |
| ], | |
| "links": { | |
| "paper": "https://arxiv.org/abs/2504.02826", | |
| "data": "https://huggingface.co/datasets/PhoenixZ/RISEBench", | |
| "outputs": "https://huggingface.co/datasets/zpy777/RISEBench_Outputs", | |
| "github": "https://github.com/VisionXLab/RISEBench/tree/main/RISEBench" | |
| }, | |
| "judges": { | |
| "instruction_reasoning": "GPT-4o", | |
| "appearance_consistency": "GPT-4o", | |
| "visual_plausibility": "GPT-4o" | |
| }, | |
| "results_by_language": { | |
| "en": { | |
| "language": "Original published results", | |
| "language_code": "en", | |
| "model_count": 20, | |
| "groups": [], | |
| "models": [ | |
| { | |
| "id": "gpt-image-1-5", | |
| "name": "GPT-Image-1.5", | |
| "group": null, | |
| "multi_image": null, | |
| "source_order": 1, | |
| "accuracy": { | |
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| "spatial": 62.0, | |
| "logical": 21.2, | |
| "total": 51.4 | |
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| "instruction_reasoning": 69.7, | |
| "appearance_consistency": 92.5, | |
| "visual_plausibility": 94.9 | |
| } | |
| }, | |
| { | |
| "id": "gpt-image-2", | |
| "name": "GPT-Image-2", | |
| "group": null, | |
| "multi_image": null, | |
| "source_order": 2, | |
| "accuracy": { | |
| "temporal": 45.9, | |
| "causal": 66.7, | |
| "spatial": 50.0, | |
| "logical": 34.1, | |
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| "instruction_reasoning": 73.8, | |
| "appearance_consistency": 89.3, | |
| "visual_plausibility": 94.9 | |
| } | |
| }, | |
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