{
  "schema_version": 2,
  "scope": {
    "audited_through": "2026-08-30",
    "include_if_any": [
      "作为机制总览、机制分章或视频基础模型主章的技术路线锚点、定义性论文或里程碑。",
      "在两个及以上机制或基础模型发布页重复支撑跨路线主张，适合作为统一 BibTeX 与代码状态入口。",
      "虽为机构技术报告或项目报告，但它是核心系统、模型家族或发布面的唯一一手出处。"
    ],
    "excluded_by_default": [
      "仅在单个任务、评测、数据集、时间线或研究记录中作局部证据的条目。",
      "二手综述、新闻、聚合页，以及与核心论文无直接对应关系的社区实现。",
      "仓库、许可证、标准或产品页本身；它们继续留在章末参考文献中，除非是核心系统唯一的一手报告。"
    ]
  },
  "sections": {
    "A": "经典视觉、运动与动态纹理",
    "B": "循环预测与物理交互",
    "C": "对抗视频生成与分布评测",
    "D": "离散表征、token 与自回归生成",
    "E": "扩散视频生成",
    "F": "潜变量世界模型与控制",
    "G": "交互式世界基础模型",
    "H": "JEPA 表征与规划",
    "I": "跨路线生成基础、测量与 tokenizer",
    "J": "现代视频基础模型与系统报告",
    "K": "因果、自回归流式生成与加速",
    "L": "Video DiT 骨干、注意力与扩展",
    "M": "变分随机视频与时序潜变量",
    "N": "开放集与单/多主体视频个性化"
  },
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        "kind": "doi",
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      "source": {
        "kind": "doi",
        "id": "10.1016/0004-3702(81)90024-2"
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      "github": null
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      "citekey": "schodl2000video",
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      "source": {
        "kind": "doi",
        "id": "10.1145/344779.345012"
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      "github": null
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      "citekey": "lucas1981iterative",
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        "kind": "manual",
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          "entry_type": "inproceedings",
          "title": "An Iterative Image Registration Technique with an Application to Stereo Vision",
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          "booktitle": "Proceedings of the 7th International Joint Conference on Artificial Intelligence (IJCAI)",
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      "citekey": "finn2016unsupervised",
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      "source": {
        "kind": "arxiv",
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      "citekey": "lotter2016deep",
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        "kind": "arxiv",
        "id": "1605.08104"
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        "url": "https://github.com/coxlab/prednet",
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      "citekey": "mathieu2015deep",
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      "source": {
        "kind": "arxiv",
        "id": "1511.05440"
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      "citekey": "shi2015convolutional",
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        "kind": "arxiv",
        "id": "1506.04214"
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      "citekey": "srivastava2015unsupervised",
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        "kind": "arxiv",
        "id": "1502.04681"
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      "citekey": "clark2019adversarial",
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        "kind": "arxiv",
        "id": "1907.06571"
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      "citekey": "tulyakov2017mocogan",
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        "kind": "arxiv",
        "id": "1707.04993"
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        "url": "https://github.com/sergeytulyakov/mocogan",
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        "kind": "arxiv",
        "id": "1609.02612"
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        "url": "https://github.com/cvondrick/videogan",
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      "source": {
        "kind": "arxiv",
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      "citekey": "villegas2022phenaki",
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        "kind": "arxiv",
        "id": "2210.02399"
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      "github": null
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      "citekey": "yan2021videogpt",
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        "kind": "arxiv",
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        "url": "https://github.com/wilson1yan/VideoGPT",
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        "note": "作者实现"
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      "citekey": "yu2022magvit",
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      "source": {
        "kind": "arxiv",
        "id": "2212.05199"
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        "url": "https://github.com/google-research/magvit",
        "status": "official-code",
        "note": "Google Research 官方实现；仓库已归档"
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    },
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      "citekey": "yu2023language",
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      "source": {
        "kind": "arxiv",
        "id": "2310.05737"
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      "github": {
        "url": "https://github.com/google-research/magvit",
        "status": "official-related-code",
        "note": "作者团队的 MAGVIT v1 仓库；README 未声明包含 MAGVIT-v2 实现；仓库已归档"
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    },
    {
      "citekey": "bartal2024lumiere",
      "section": "E",
      "source": {
        "kind": "arxiv",
        "id": "2401.12945"
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      "citekey": "blattmann2023align",
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      "source": {
        "kind": "arxiv",
        "id": "2304.08818"
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      "github": null
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      "citekey": "blattmann2023stable",
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      "source": {
        "kind": "arxiv",
        "id": "2311.15127"
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        "url": "https://github.com/Stability-AI/generative-models",
        "status": "official-code",
        "note": "Stability AI 官方模型仓库"
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        "kind": "arxiv",
        "id": "2307.04725"
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        "url": "https://github.com/guoyww/AnimateDiff",
        "status": "official-code",
        "note": "作者实现"
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      "citekey": "ho2020denoising",
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      "source": {
        "kind": "arxiv",
        "id": "2006.11239"
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      "github": {
        "url": "https://github.com/hojonathanho/diffusion",
        "status": "official-code",
        "note": "作者实现"
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    },
    {
      "citekey": "ho2022imagen",
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      "source": {
        "kind": "arxiv",
        "id": "2210.02303"
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      "github": null
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    {
      "citekey": "ho2022video",
      "section": "E",
      "source": {
        "kind": "arxiv",
        "id": "2204.03458"
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      "github": {
        "url": "https://github.com/lucidrains/video-diffusion-pytorch",
        "status": "community-implementation",
        "note": "第三方复现；未发现论文作者公开的官方实现"
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    {
      "citekey": "singer2022make",
      "section": "E",
      "source": {
        "kind": "arxiv",
        "id": "2209.14792"
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      "github": null
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      "citekey": "openai2024sora",
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      "source": {
        "kind": "manual",
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          "entry_type": "misc",
          "title": "Video Generation Models as World Simulators",
          "authors": "{OpenAI}",
          "year": "2024",
          "howpublished": "Technical report",
          "url": "https://openai.com/index/video-generation-models-as-world-simulators/"
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      "github": null
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      "citekey": "bommasani2021opportunities",
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      "source": {
        "kind": "arxiv",
        "id": "2108.07258"
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      "github": null
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    {
      "citekey": "hafner2018learning",
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      "source": {
        "kind": "arxiv",
        "id": "1811.04551"
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      "github": {
        "url": "https://github.com/google-research/planet",
        "status": "official-code",
        "note": "Google Research 官方实现；仓库已归档"
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      "citekey": "hafner2019dream",
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      "source": {
        "kind": "arxiv",
        "id": "1912.01603"
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        "url": "https://github.com/danijar/dreamer",
        "status": "official-code",
        "note": "作者实现"
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    {
      "citekey": "hafner2023mastering",
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      "source": {
        "kind": "arxiv",
        "id": "2301.04104"
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      "github": {
        "url": "https://github.com/danijar/dreamerv3",
        "status": "official-code",
        "note": "作者实现"
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      "citekey": "hansen2023tdmpc2",
      "section": "F",
      "source": {
        "kind": "arxiv",
        "id": "2310.16828"
      },
      "github": {
        "url": "https://github.com/nicklashansen/tdmpc2",
        "status": "official-code",
        "note": "作者实现，含多任务 checkpoint 与数据"
      }
    },
    {
      "citekey": "hu2023gaia",
      "section": "F",
      "source": {
        "kind": "arxiv",
        "id": "2309.17080"
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      "github": null
    },
    {
      "citekey": "schrittwieser2020mastering",
      "section": "F",
      "source": {
        "kind": "doi",
        "id": "10.1038/s41586-020-03051-4"
      },
      "github": {
        "url": "https://github.com/werner-duvaud/muzero-general",
        "status": "community-implementation",
        "note": "第三方通用实现；DeepMind 仅公开伪代码，未公开完整官方训练仓库"
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    {
      "citekey": "oh2015actionconditional",
      "section": "F",
      "source": {
        "kind": "manual",
        "metadata": {
          "entry_type": "inproceedings",
          "title": "Action-Conditional Video Prediction using Deep Networks in Atari Games",
          "authors": "Junhyuk Oh and Xiaoxiao Guo and Honglak Lee and Richard Lewis and Satinder Singh",
          "year": "2015",
          "booktitle": "Advances in Neural Information Processing Systems 28",
          "url": "https://papers.nips.cc/paper_files/paper/2015/hash/6ba3af5d7b2790e73f0de32e5c8c1798-Abstract.html"
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      },
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        "url": "https://github.com/junhyukoh/nips2015-action-conditional-video-prediction",
        "status": "official-code",
        "note": "作者实现"
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    {
      "citekey": "ha2018worldmodels",
      "section": "F",
      "source": {
        "kind": "arxiv",
        "id": "1803.10122"
      },
      "github": {
        "url": "https://github.com/hardmaru/WorldModelsExperiments",
        "status": "official-research-artifact",
        "note": "作者发布的实验代码与笔记"
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    },
    {
      "citekey": "bruce2024genie",
      "section": "G",
      "source": {
        "kind": "arxiv",
        "id": "2402.15391"
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      "github": null
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      "citekey": "nvidia2025cosmos",
      "section": "G",
      "source": {
        "kind": "arxiv",
        "id": "2501.03575"
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      "github": {
        "url": "https://github.com/nvidia-cosmos/cosmos-predict1",
        "status": "official-code",
        "note": "NVIDIA Cosmos Predict1 官方实现"
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    },
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      "citekey": "nvidia2026cosmos3",
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      "source": {
        "kind": "arxiv",
        "id": "2606.02800",
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        "url": "https://github.com/NVIDIA/Cosmos",
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      "citekey": "valevski2024diffusion",
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        "kind": "arxiv",
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        "url": "https://github.com/GameNGen/GameNGen.github.io",
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        "kind": "arxiv",
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        "kind": "arxiv",
        "id": "2602.15922"
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        "url": "https://github.com/dreamzero0/dreamzero",
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        "note": "DreamZero / World Action Model 作者实现"
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        "kind": "manual",
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          "entry_type": "misc",
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      "github": null
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      "citekey": "deepmind2025genie3",
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        "kind": "manual",
        "metadata": {
          "entry_type": "misc",
          "title": "Genie 3: A New Frontier for World Models",
          "authors": "{Google DeepMind}",
          "year": "2025",
          "howpublished": "Project report",
          "url": "https://deepmind.google/blog/genie-3-a-new-frontier-for-world-models/"
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      },
      "github": null
    },
    {
      "citekey": "nvidia2025cosmospredict2",
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      "source": {
        "kind": "manual",
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          "entry_type": "misc",
          "title": "Develop Custom Physical AI Foundation Models with NVIDIA Cosmos Predict-2",
          "authors": "{NVIDIA}",
          "year": "2025",
          "howpublished": "Technical release",
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      },
      "github": {
        "url": "https://github.com/nvidia-cosmos/cosmos-predict2",
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        "note": "NVIDIA Cosmos 官方实现"
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      "citekey": "runway2025gwm1",
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        "kind": "manual",
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          "entry_type": "misc",
          "title": "Introducing Runway GWM-1",
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          "year": "2025",
          "howpublished": "Project report",
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      },
      "github": null
    },
    {
      "citekey": "worldlabs2025marble",
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        "kind": "manual",
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          "entry_type": "misc",
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          "howpublished": "Official research release",
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      },
      "github": null
    },
    {
      "citekey": "assran2023selfsupervised",
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      "source": {
        "kind": "arxiv",
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        "url": "https://github.com/facebookresearch/ijepa",
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        "note": "Meta AI Research 官方 I-JEPA 实现；仓库已归档"
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    },
    {
      "citekey": "assran2025vjepa2",
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      "source": {
        "kind": "arxiv",
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        "url": "https://github.com/facebookresearch/vjepa2",
        "status": "official-code",
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      "source": {
        "kind": "arxiv",
        "id": "2510.00739"
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        "url": "https://github.com/facebookresearch/td_jepa",
        "status": "official-code",
        "note": "论文官方零样本强化学习实现"
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    {
      "citekey": "balestriero2025lejepa",
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      "source": {
        "kind": "arxiv",
        "id": "2511.08544"
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      "github": {
        "url": "https://github.com/galilai-group/lejepa",
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        "note": "LeJEPA 与 SIGReg 官方实现"
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    },
    {
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        "kind": "arxiv",
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    {
      "citekey": "bardes2024revisiting",
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        "kind": "arxiv",
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      "github": {
        "url": "https://github.com/facebookresearch/jepa",
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        "note": "Meta AI Research 官方实现"
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    },
    {
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        "kind": "arxiv",
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        "url": "https://github.com/lucas-maes/le-wm",
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        "note": "LeWorldModel 官方实现"
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    },
    {
      "citekey": "murlabadia2026vjepa21",
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      "source": {
        "kind": "arxiv",
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      },
      "github": {
        "url": "https://github.com/facebookresearch/vjepa2",
        "status": "official-code",
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    },
    {
      "citekey": "terver2026lightweight",
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      "source": {
        "kind": "arxiv",
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      "github": {
        "url": "https://github.com/facebookresearch/eb_jepa",
        "status": "official-code",
        "note": "Meta FAIR 官方轻量教学与研究库"
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    },
    {
      "citekey": "zhou2024dinowm",
      "section": "H",
      "source": {
        "kind": "arxiv",
        "id": "2411.04983"
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      "github": {
        "url": "https://github.com/gaoyuezhou/dino_wm",
        "status": "official-code",
        "note": "作者实现"
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    },
    {
      "citekey": "lecun2022path",
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      "source": {
        "kind": "manual",
        "metadata": {
          "entry_type": "misc",
          "title": "A Path Towards Autonomous Machine Intelligence",
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      "github": null
    },
    {
      "citekey": "kingma2013autoencoding",
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      "source": {
        "kind": "arxiv",
        "id": "1312.6114"
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    },
    {
      "citekey": "huszar2015how",
      "section": "I",
      "source": {
        "kind": "arxiv",
        "id": "1511.05101"
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      "github": null
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    {
      "citekey": "unterthiner2018towards",
      "section": "I",
      "source": {
        "kind": "arxiv",
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    {
      "citekey": "song2020scorebased",
      "section": "I",
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        "id": "2402.13929"
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    {
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      "source": {
        "kind": "arxiv",
        "id": "2403.12706"
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      "github": null
    },
    {
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      "source": {
        "kind": "arxiv",
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    {
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      "source": {
        "kind": "arxiv",
        "id": "2607.14088"
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      "github": null
    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2608.05798"
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      "github": null
    },
    {
      "citekey": "guo2026vrae",
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      "source": {
        "kind": "arxiv",
        "id": "2608.13556"
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      "github": null
    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2410.13720"
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      "github": null
    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2412.03603"
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      "github": {
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        "status": "official-code",
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    },
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      "source": {
        "kind": "arxiv",
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      "github": {
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      "github": {
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    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2503.09642"
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      "github": {
        "url": "https://github.com/hpcaitech/Open-Sora",
        "status": "official-code",
        "note": "Open-Sora 2.0 官方训练代码与 checkpoints"
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    },
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      "source": {
        "kind": "arxiv",
        "id": "2503.20314"
      },
      "github": {
        "url": "https://github.com/Wan-Video/Wan2.1",
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      "source": {
        "kind": "arxiv",
        "id": "2504.13074"
      },
      "github": {
        "url": "https://github.com/SkyworkAI/SkyReels-V2",
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    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2505.13211"
      },
      "github": {
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    },
    {
      "citekey": "low2025ovi",
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      "source": {
        "kind": "arxiv",
        "id": "2510.01284"
      },
      "github": {
        "url": "https://github.com/character-ai/Ovi",
        "status": "official-code",
        "note": "Character.AI 官方代码与权重"
      }
    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2511.18870"
      },
      "github": {
        "url": "https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5",
        "status": "official-code",
        "note": "腾讯混元 1.5 官方代码、权重与训练更新"
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    },
    {
      "citekey": "hacohen2026ltx2",
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      "source": {
        "kind": "arxiv",
        "id": "2601.03233"
      },
      "github": {
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        "note": "Lightricks 官方音视频推理与 LoRA 训练仓库"
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    },
    {
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      "source": {
        "kind": "arxiv",
        "id": "2601.17323"
      },
      "github": {
        "url": "https://github.com/SkyworkAI/SkyReels-V3",
        "status": "official-code",
        "note": "Skywork AI 官方推理代码与任务权重"
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    },
    {
      "citekey": "seedance2026seedance2",
      "section": "J",
      "source": {
        "kind": "arxiv",
        "id": "2604.14148"
      },
      "github": null
    },
    {
      "citekey": "chen2024diffusionforcing",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2407.01392"
      },
      "github": {
        "url": "https://github.com/buoyancy99/diffusion-forcing",
        "status": "official-code",
        "note": "论文作者发布的官方实现"
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    },
    {
      "citekey": "yin2024causvid",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2412.07772"
      },
      "github": {
        "url": "https://github.com/tianweiy/CausVid",
        "status": "official-code",
        "note": "CausVid / CVPR 2025 官方实现"
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    },
    {
      "citekey": "huang2025selfforcing",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2506.08009"
      },
      "github": {
        "url": "https://github.com/guandeh17/Self-Forcing",
        "status": "official-code",
        "note": "NeurIPS 2025 论文官方实现"
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    },
    {
      "citekey": "yang2025longlive",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2509.22622"
      },
      "github": {
        "url": "https://github.com/NVlabs/LongLive",
        "status": "official-code",
        "note": "NVIDIA Research 官方代码与长视频基础设施"
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    },
    {
      "citekey": "liu2025rollingforcing",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2509.25161"
      },
      "github": null
    },
    {
      "citekey": "yu2025videossm",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2512.04519"
      },
      "github": null
    },
    {
      "citekey": "samuel2026fastautoregressive",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2602.01801"
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      "github": null
    },
    {
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      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2602.02214"
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      "github": {
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        "status": "official-code",
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    },
    {
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      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2602.02958"
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      "github": null
    },
    {
      "citekey": "lv2026lightforcing",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2602.04789"
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      "github": null
    },
    {
      "citekey": "li2026rollingsink",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2602.07775"
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      "github": null
    },
    {
      "citekey": "xu2026sparseforcing",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2604.21221"
      },
      "github": null
    },
    {
      "citekey": "xue2026systematic",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2604.25427"
      },
      "github": null
    },
    {
      "citekey": "ji2026forcingkv",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2605.09681"
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      "github": null
    },
    {
      "citekey": "zhao2026causalforcingpp",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2605.15141"
      },
      "github": {
        "url": "https://github.com/thu-ml/Causal-Forcing",
        "status": "official-code",
        "note": "与 Causal Forcing 共用官方仓库；README 明确覆盖 Causal Forcing++"
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    },
    {
      "citekey": "li2026attendlocally",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2605.16579"
      },
      "github": null
    },
    {
      "citekey": "yesiltepe2026videomla",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2605.30351"
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      "github": null
    },
    {
      "citekey": "hu2026longliverag",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2606.02553"
      },
      "github": null
    },
    {
      "citekey": "yu2026videomirai",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2606.03971"
      },
      "github": null
    },
    {
      "citekey": "li2026aad1",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2606.03972"
      },
      "github": null
    },
    {
      "citekey": "lu2026fademem",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2606.10671"
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      "github": null
    },
    {
      "citekey": "zheng2026causalrcm",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2606.25473"
      },
      "github": {
        "url": "https://github.com/NVlabs/rcm",
        "status": "official-code",
        "note": "NVIDIA Research 官方 rCM / Causal-rCM 代码与配方"
      }
    },
    {
      "citekey": "fiebelman2026mvforcing",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2607.05376"
      },
      "github": null
    },
    {
      "citekey": "zhuang2026selfgradient",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2607.20368"
      },
      "github": null
    },
    {
      "citekey": "xiao2026joyaivideoedit",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2608.03974"
      },
      "github": null
    },
    {
      "citekey": "ban2026stream4d",
      "section": "K",
      "source": {
        "kind": "arxiv",
        "id": "2608.19556"
      },
      "github": null
    },
    {
      "citekey": "peebles2022scalable",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2212.09748"
      },
      "github": {
        "url": "https://github.com/facebookresearch/DiT",
        "status": "official-code",
        "note": "作者官方 DiT 实现；仓库已归档"
      }
    },
    {
      "citekey": "gupta2023photorealistic",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2312.06662"
      },
      "github": null
    },
    {
      "citekey": "ma2024latte",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2401.03048",
        "metadata_override": {
          "journal": "Transactions on Machine Learning Research"
        }
      },
      "github": {
        "url": "https://github.com/Vchitect/Latte",
        "status": "official-code",
        "note": "作者官方 Latte 训练与推理实现"
      }
    },
    {
      "citekey": "yang2024cogvideox",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2408.06072"
      },
      "github": {
        "url": "https://github.com/zai-org/CogVideo",
        "status": "official-code",
        "note": "智谱官方 CogVideoX 代码、权重与训练入口"
      }
    },
    {
      "citekey": "chen2025sanavideo",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2509.24695"
      },
      "github": {
        "url": "https://github.com/NVlabs/Sana",
        "status": "official-code",
        "note": "NVIDIA Research 官方 SANA 与 SANA-Video 实现和权重入口"
      }
    },
    {
      "citekey": "huang2025linvideo",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2510.08318"
      },
      "github": null
    },
    {
      "citekey": "mao2025timeripples",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2511.12035"
      },
      "github": null
    },
    {
      "citekey": "chen2026sanavideo2",
      "section": "L",
      "source": {
        "kind": "arxiv",
        "id": "2607.21553"
      },
      "github": {
        "url": "https://github.com/NVlabs/Sana",
        "status": "official-code",
        "note": "官方统一仓库；具体已发布 checkpoint 仍须按模型文档核对"
      }
    },
    {
      "citekey": "chung2015recurrent",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "1506.02216"
      },
      "github": {
        "url": "https://github.com/jych/nips2015_vrnn",
        "status": "official-code",
        "note": "作者发布的旧版 Theano 实现"
      }
    },
    {
      "citekey": "babaeizadeh2017stochastic",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "1710.11252"
      },
      "github": {
        "url": "https://github.com/tensorflow/tensor2tensor",
        "status": "official-code",
        "note": "SV2P 位于该官方仓库；仓库已归档且标记为弃用"
      }
    },
    {
      "citekey": "denton2018stochastic",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "1802.07687"
      },
      "github": {
        "url": "https://github.com/edenton/svg",
        "status": "official-code",
        "note": "作者实现"
      }
    },
    {
      "citekey": "lee2018stochastic",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "1804.01523"
      },
      "github": {
        "url": "https://github.com/alexlee-gk/video_prediction",
        "status": "official-code",
        "note": "作者发布的 SAVP 官方实现"
      }
    },
    {
      "citekey": "castrejon2019improved",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "1904.12165"
      },
      "github": {
        "url": "https://github.com/facebookresearch/improved_vrnn",
        "status": "official-code",
        "note": "作者配套实现；仓库已归档"
      }
    },
    {
      "citekey": "franceschi2020stochastic",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "2002.09219"
      },
      "github": {
        "url": "https://github.com/edouardelasalles/srvp",
        "status": "official-code",
        "note": "作者实现，并提供预训练模型入口"
      }
    },
    {
      "citekey": "wu2021greedy",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "2103.04174"
      },
      "github": null
    },
    {
      "citekey": "saxena2021clockwork",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "2102.09532"
      },
      "github": {
        "url": "https://github.com/vaibhavsaxena11/cwvae",
        "status": "official-code",
        "note": "第一作者发布的训练与评测实现"
      }
    },
    {
      "citekey": "daniel2026latent",
      "section": "M",
      "source": {
        "kind": "arxiv",
        "id": "2603.04553"
      },
      "github": {
        "url": "https://github.com/taldatech/lpwm",
        "status": "official-code",
        "note": "ICLR 2026 Oral 官方代码、数据与 checkpoints"
      }
    },
    {
      "citekey": "wang2024customvideo",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2401.09962"
      },
      "github": null
    },
    {
      "citekey": "ma2024magicme",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2402.09368"
      },
      "github": {
        "url": "https://github.com/Zhen-Dong/Magic-Me",
        "status": "official-code",
        "note": "作者官方 VCD 训练与推理实现；依赖第三方 SD/AnimateDiff 权重，并提供若干身份嵌入；未发布训练数据集"
      }
    },
    {
      "citekey": "li2024personalvideo",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2411.17048"
      },
      "github": {
        "url": "https://github.com/EchoPluto/PersonalVideo",
        "status": "official-project-page",
        "note": "作者占位仓；README 的 Code 仍为 Coming Soon，未发布实现、权重或数据"
      }
    },
    {
      "citekey": "chen2025videoalchemist",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2501.06187"
      },
      "github": {
        "url": "https://github.com/snap-research/MSRVTT-Personalization",
        "status": "official-research-artifact",
        "note": "官方 MSRVTT-Personalization 测试集与评测协议；不含 Video Alchemist 模型实现或权重"
      }
    },
    {
      "citekey": "liang2025movie",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2502.07802"
      },
      "github": null
    },
    {
      "citekey": "deng2025magref",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2505.23742"
      },
      "github": {
        "url": "https://github.com/MAGREF-Video/MAGREF",
        "status": "official-code",
        "note": "官方推理代码与 MAGREF checkpoint；480P/14B Pro checkpoint 和训练代码仍在 TODO，训练数据未发布"
      }
    },
    {
      "citekey": "girish2025alchemint",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2512.10943"
      },
      "github": {
        "url": "https://github.com/snap-research/Video-AlcheMinT",
        "status": "official-project-page",
        "note": "官方 README/项目占位仓；未发布方法代码、权重或 benchmark 数据"
      }
    },
    {
      "citekey": "huang2026rethinking",
      "section": "N",
      "source": {
        "kind": "arxiv",
        "id": "2604.03738"
      },
      "github": {
        "url": "https://github.com/byhuang123/PoCo",
        "status": "official-project-page",
        "note": "官方占位与演示仓；Release Plan 中 Core model code 尚未发布，无权重或数据"
      }
    }
  ]
}