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    "slug": "kadrey-v-meta",
    "titleZh": "卡德里等诉 Meta 案",
    "formalName": "Kadrey et al. v. Meta Platforms, Inc.",
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      "Kadrey v. Meta"
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    "professionalSummary": "争点包括训练复制是否构成合理使用、影子图书馆下载及潜在市场损害。地区法院裁判仅处理案内特定主张和记录；截至 2026 年 7 月，合理使用裁判尚未形成已经受理的上诉判决。",
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        "title": "Kadrey v. Meta Platforms — Order on partial summary judgment",
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      "narrativeZh": "多名作家指控 Meta 使用含其作品的数据训练 Llama，并把影子图书馆取得、训练复制和潜在图书市场损害纳入同一诉讼。地区法院在 2025 年依当时提交的证据向 Meta 作出部分简易判决，但案件仍有其他请求和程序。",
      "partiesZh": [
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      "proceduralOriginZh": "作家以 3:23-cv-03417-VC 起诉；地区法院于 2025 年 6 月 25 日就部分训练复制主张作出简易判决。",
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        "titleZh": "Llama 训练是否构成合理使用",
        "questionZh": "在本案具体证据记录上，复制书籍训练 Llama 是否受合理使用保护？",
        "contextZh": "法院把合理使用判断与具体用途及市场证据相联系，并未建立所有模型训练当然合理使用的规则。",
        "topic": "copyright",
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        "courtTreatmentZh": "地区法院在当时记录上就原告的训练复制主张向 Meta 作出部分简易判决；其他请求和程序仍继续。",
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            "sideZh": "Meta",
            "positionZh": "在部分简易判决程序中取得有利结果，法院依当时提交的记录未让该训练复制主张继续。",
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        "matterId": "matter-04",
        "titleZh": "影子图书馆副本的取得",
        "questionZh": "被指从影子图书馆下载书籍的行为，是否形成独立于后续训练用途的侵权责任？",
        "contextZh": "作品如何取得与训练目的是否具有转换性是不同问题；训练合理使用结论不能自动消除取得阶段责任。",
        "topic": "copyright",
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            "sideZh": "原告作家",
            "positionZh": "把影子图书馆下载作为未经授权复制的重要事实基础。",
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            "documentIds": []
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            "id": "matter-04:issue-shadow-library-acquisition:position-2",
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            "positionZh": "现有公开材料未见其对取得阶段责任作出可据以概括的明确回应；本案卷不代为补写。",
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        "questionZh": "原告能否证明 Llama 训练或模型能力对作品市场及潜在训练许可市场造成法律上可识别的损害？",
        "contextZh": "地区法院强调合理使用高度依赖案内市场证据，市场损害不能仅由作品被用于训练推定。",
        "topic": "copyright",
        "status": "partly-resolved",
        "courtTreatmentZh": "法院依当时提交的市场证据作出部分简易判决，但明确其判断受具体记录限制。",
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            "id": "matter-04:issue-market-harm-evidence:position-2",
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        "outcomeZh": "地区法院根据当时提交的证据，就原告针对 Llama 训练复制的特定主张向 Meta 作出部分简易判决。",
        "holdingsZh": [
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        ],
        "reasoningZh": [
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          "原告在当时记录中提交的市场证据不足以把该项训练复制主张留待审判，但这一判断不脱离本案证据而普遍化。"
        ],
        "reliefZh": "就被处理的训练复制主张给予 Meta 部分简易判决；未就案件其余请求提供全案终局救济。",
        "scopeAndLimitsZh": "仅约束本案当事人在当时证据记录下的特定主张；不处理所有数据取得方式，也不构成通用模型训练的当然豁免。",
        "precedentialWeight": "persuasive",
        "appealStatusZh": "案件仍在地区法院推进；截至现有案卷日期，没有已经受理并作出裁判的上诉判决。",
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        "issueId": "matter-04:issue-training-fair-use",
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        "title": "生成式 AI 遇上版权法",
        "originalTitle": "Generative AI Meets Copyright",
        "url": "https://doi.org/10.1126/science.adi0656",
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        "publishedAt": "2023-07-14",
        "author": "Pamela Samuelson",
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          "venue": "Science 381(6654): 158–161",
          "publisher": "American Association for the Advancement of Science",
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        "author": "Peter Henderson; Xuechen Li; Dan Jurafsky; Tatsunori Hashimoto; Mark A. Lemley; Percy Liang",
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        "identifiers": {},
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          "abstractZh": "把合理使用 doctrine 与模型输出相似度实验放在同一框架中，认为训练和部署风险取决于输出、市场影响与缓解措施，法律和技术护栏需要共同演进。",
          "venue": "Journal of Machine Learning Research 24(400): 1–79",
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        "identifiers": {},
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        "metadata": {
          "abstractZh": "把合理使用 doctrine 与模型输出相似度实验放在同一框架中，认为训练和部署风险取决于输出、市场影响与缓解措施，法律和技术护栏需要共同演进。",
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        "relevanceSummaryZh": "为训练复制属于非表达性使用的主张提供基础 doctrine，同时明确表达性模仿可能改变结论。 本次规则匹配仅使用本争点文本及其引用主张，命中 1 个确定性争点词；AI 作用分面只用于候选召回。",
        "viewpoint": "supportive",
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        "author": "Mark A. Lemley; Bryan Casey",
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        "metadata": {
          "abstractZh": "主张机器为获取不受版权保护的事实、思想或功能而学习时，训练复制原则上应得到合理使用的有利评价；若训练目标是复现受保护表达，结论会更困难。",
          "venue": "Texas Law Review, Volume 99, Issue 4",
          "publisher": "Texas Law Review Association",
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        "author": "Katrina Geddes",
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          "abstractZh": "文章分别分析未经许可训练、近似输出、版权管理信息、商标和形象商业利用，强调开发者、部署者与用户的责任不能用一个统一答案概括。",
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        "documentId": "knowledge-generative-ai-meets-copyright",
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