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  "name": "apple-pi-full",
  "description": "Apple-Pi (Full): a physics benchmark of 400 cases (243 simulation + 157 realworld) 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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  "url": "https://huggingface.co/datasets/AnonymousSubmitt/apple-pi-full",
  "version": "1.0.0",
  "datePublished": "2026-05-07",
  "citeAs": "@misc{anonymous2026applepi, title={Apple-Pi: Physics Infographics Benchmark}, author={Anonymous}, year={2026}}",
  "creator": {
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    "name": "Anonymous"
  },
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    "physics reasoning",
    "video generation",
    "image generation",
    "benchmark",
    "evaluation"
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  "rai:dataLimitations": "Apple-Pi is intended for evaluation, 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 covers nine simulation tasks and seven realworld categories with case counts measured per category; common phenomena (projectile, freefall) are more represented than rarer composition or multi-body collision cases. Synthetic cases use a curated 76-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.",
  "rai:hasSyntheticData": true,
  "prov:wasDerivedFrom": [
    {
      "@type": "prov:Entity",
      "prov:label": "Original recordings (no upstream source dataset)",
      "sc:description": "This dataset is not derived from any external public dataset. Synthetic cases are originally generated using NVIDIA Isaac Sim (a 3D rigid-body physics simulator). Realworld cases are originally recorded video clips collected under controlled laboratory conditions."
    }
  ],
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      "prov:atTime": "2025/2026",
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      "prov:label": "Realworld video recording",
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      "prov:atTime": "2025/2026",
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      "sha256": "https://github.com/mlcommons/croissant/issues/80"
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