CoTGuard：利用思维链触发在多智能体LLM系统中实现版权保护
CoTGuard: Using Chain-of-Thought Triggering for Copyright Protection in Multi-Agent LLM Systems
AI总结：
CoTGuard通过思维链触发检测多智能体系统中的版权内容泄漏，实现细粒度监控且对任务性能干扰最小。
摘要：
随着大型语言模型（LLMs）演变为能够进行协作推理和任务执行的自主智能体，多智能体LLM系统已成为解决复杂问题的强大范式。然而，这些系统对版权保护提出了新的挑战，尤其是在敏感或受版权保护的内容通过智能体间的通信和推理被无意中回忆时。现有的保护技术主要集中于检测最终输出中的内容，忽视了智能体内部更丰富、更具揭示性的推理过程。在本文中，我们介绍了CoTGuard，一种新颖的版权保护框架，利用思维链（CoT）推理中的触发式检测。具体而言，我们通过将特定触发查询嵌入智能体提示中，能够激活特定的CoT片段并监控中间推理步骤，以检测未经授权的内容复制。这种方法能够在协作智能体场景中实现细粒度、可解释的版权违规检测。我们在多种基准上进行了广泛实验评估CoTGuard，结果表明它能有效揭示内容泄漏，同时对任务性能的干扰最小。我们的研究结果表明，推理级监控为保护基于LLM的智能体系统中的知识产权提供了一个有前景的方向。
英文摘要：
As large language models (LLMs) evolve into autonomous agents capable of collaborative reasoning and task execution, multi-agent LLM systems have emerged as a powerful paradigm for solving complex problems. However, these systems pose new challenges for copyright protection, particularly when sensitive or copyrighted content is inadvertently recalled through inter-agent communication and reasoning. Existing protection techniques primarily focus on detecting content in final outputs, overlooking the richer, more revealing reasoning processes within the agents themselves. In this paper, we introduce CoTGuard, a novel framework for copyright protection that leverages trigger-based detection within Chain-of-Thought (CoT) reasoning. Specifically, we can activate specific CoT segments and monitor intermediate reasoning steps for unauthorized content reproduction by embedding specific trigger queries into agent prompts. This approach enables fine-grained, interpretable detection of copyright violations in collaborative agent scenarios. We evaluate CoTGuard on various benchmarks in extensive experiments and show that it effectively uncovers content leakage with minimal interference to task performance. Our findings suggest that reasoning-level monitoring offers a promising direction for safeguarding intellectual property in LLM-based agent systems.
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