使用大语言模型探测风格挪用：欧盟法律下版权侵权的评估框架
Probing Stylistic Appropriation using Large Language Models: An Evaluation Framework for Copyright Infringement under EU Law
AI总结：
提出PSALM框架，通过十个评估器将欧盟版权法标准操作化，发现指令调优模型在接触语料前已有非平凡风格相似性，微调导致系统性风格挪用，负偏好优化可降低但残留可检测风格模式。
摘要：
在网页规模语料上训练的大语言模型（LLM）可能生成侵犯版权的输出，但现有技术保障措施狭隘地集中于逐字记忆。欧盟版权学说适用更广泛的标准：实质性相似，这延伸到风格选择、叙事结构和创造性阐述。当前方法能检测的内容与法律保护的内容之间的不匹配留下了显著的合规差距。我们引入PSALM，一个LLM作为法官的框架，通过十个评估者将欧盟版权学说操作化，评估计算重叠、风格维度（写作风格、叙事声音）、内容维度（角色、情节、场景、世界构建）以及法定例外（戏仿、模仿、引用、场景必至）。将PSALM应用于在翻译的历史荷兰文学作品上微调的Llama~3.2模型，我们发现：1）指令调优模型在接触语料之前就表现出非平凡的风格相似性基线；2）微调在所有侵权相关维度上诱导系统的风格挪用，超出逐字记忆延伸到抽象叙事模式；3）负偏好优化遗忘大幅降低相似性，但留下可检测的残留风格模式。这些发现表明，仅针对字面复制的保障措施不足以缓解更广泛的版权风险。PSALM为可审计、法律知情的合规评估提供了基础设施，尽管自动相似性评分与侵权判定之间的关系需要法律专家验证。这项工作弥合了定性法律标准与定量技术测量之间的鸿沟，揭示了生成式AI与欧盟知识产权法之间的根本张力。
英文摘要：
Large language models (LLM) trained on web-scale corpora generate output that may infringe copyright, yet existing technical safeguards focus narrowly on verbatim memorisation. EU copyright doctrine applies a broader standards: substantial similarity, which extends to stylistic choices, narrative structure, and creative elaboration. This mismatch between what current methods detect and what the law protects leaves a significant compliance gap. We introduce PSALM, an LLM-as-a-judge framework that operationalises EU copyright doctrine through ten evaluators assessing computational overlap, stylistic dimensions (writing style, narrative voice), content dimensions (character, plot, scene, world building), and statutory exceptions (parody, pastiche, quotation, scènes à faire). Applying PSALM to Llama~3.2 models fine-tuned on translated historical Dutch literary works, we find that: 1) instruction-tuned models exhibit non-trivial baseline stylistic similarity prior to corpus exposure; 2) fine-tuning induces systematic stylistic appropriation across all infringement-relevant dimensions, extending beyond verbatim memorisation to abstract narrative patterns; 3) Negative Preference Optimisation unlearning substantially reduces similarity but leaves detectable residual stylistic patterns. These findings indicate that safeguards targeting literal copying alone are insufficient to mitigate broader copyright risks. PSALM provides infrastructure for auditable, legally informed compliance evaluation, though the relationship between automated similarity scores and infringement determinations requires validation by legal experts. This work bridges qualitative legal standards and quantitative technical measurement, exposing fundamental tensions between generative AI and EU intellectual property law.
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