版权侦探：一种用于证据LLM闪烁版权泄露风险的取证系统
Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage Risks
AI总结：
Copyright Detective 是一种交互式系统，用于检测和可视化LLM输出中的版权风险，通过整合多种检测方法实现系统性审计。
摘要：
我们提出了Copyright Detective，这是第一个交互式取证系统，用于检测、分析和可视化LLM输出中的潜在版权风险。该系统将版权侵权与合规视为证据发现过程，而非静态分类任务，这源于版权法的复杂性。它集成了多种检测范式，包括内容回忆测试、改写层面相似性分析、说服性牢笼探测和去学习验证，这些范式在统一且可扩展的框架内整合。通过交互式提示、响应收集和迭代工作流，我们的系统能够系统性地审计原文记忆和改写层面的泄露，支持负责任的部署和透明的LLM版权风险评估，即使在黑盒访问的情况下。
英文摘要：
We present Copyright Detective, the first interactive forensic system for detecting, analyzing, and visualizing potential copyright risks in LLM outputs. The system treats copyright infringement versus compliance as an evidence discovery process rather than a static classification task due to the complex nature of copyright law. It integrates multiple detection paradigms, including content recall testing, paraphrase-level similarity analysis, persuasive jailbreak probing, and unlearning verification, within a unified and extensible framework. Through interactive prompting, response collection, and iterative workflows, our system enables systematic auditing of verbatim memorization and paraphrase-level leakage, supporting responsible deployment and transparent evaluation of LLM copyright risks even with black-box access.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
