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| "name": "apple-pi", |
| "description": "Apple-Pi is an evaluation subset of a larger physics benchmark for evaluating physics reasoning in image and video generation models. Each case provides a video clip (or rendered frames) with ground-truth annotations of physical parameters, instance segmentation, and per-frame velocity. Released for double-blind submission.", |
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| "datePublished": "2026-05-06", |
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| "name": "Anonymous" |
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| "physics reasoning", |
| "video generation", |
| "image generation", |
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| "rai:dataLimitations": "This subset is intended for evaluation only, not training. Synthetic cases are generated with NVIDIA Isaac Sim (rigid-body dynamics) and do not capture deformation or fluid dynamics. Realworld cases are short controlled clips with limited environmental diversity. Not recommended for safety-critical or clinical applications.", |
| "rai:dataBiases": "Task distribution is weighted toward common phenomena (projectile, freefall) and may under-represent rarer tasks (composition, multi-body collision). Synthetic cases use a fixed object/material library; realworld cases are recorded under controlled lighting. No demographic bias because no humans are present.", |
| "rai:personalSensitiveInformation": "None. Synthetic cases contain no people; realworld videos do not show identifiable individuals.", |
| "rai:dataUseCases": "Evaluating physics reasoning in image- and video-generation models across perception, comprehension, and generation tracks. Validated for zero-shot benchmark evaluation. Not validated for training, clinical decision-making, or robotic control.", |
| "rai:dataSocialImpact": "Positive: provides a controlled benchmark to measure physics understanding gaps in current generation models. Risk: scores may be over-interpreted as general physics reasoning ability. Mitigation: released under CC BY-SA 4.0 with explicit research-evaluation framing; contains no humans or sensitive content.", |
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| "prov:atTime": "2025/2026", |
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