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English(EN) TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories

新的TRACE水印确保LLM代理轨迹的来源

研究人员开发了TRACE,一种新颖的双通道水印,旨在确保LLM代理轨迹的来源。该系统能够抵御可能试图重新品牌化或替换代理的对手,因为它将水印直接嵌入到轨迹日志中。TRACE利用一个基于局部内容进行无失真动作选择的选择通道,以及一个基于日志骨架以在重写下保持不变的计数通道,从而确保即使日志被篡改也能进行归因。 AI

影响 该水印系统可以增强LLM代理部署中的信任和问责制,特别是在涉及第三方经销商的情况下。

排序理由 该集群描述了一篇详细介绍LLM代理轨迹水印的新颖技术方法的学术论文。

在 arXiv cs.AI 阅读 →

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新的TRACE水印确保LLM代理轨迹的来源

报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Zheng Gao, Xiaoyu Li, Xiaoyan Feng, Jiaojiao Jiang, Yang Song, Yulei Sui, Zhenchang Xing, Liming Zhu ·

    TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories

    arXiv:2607.08400v1 Announce Type: cross Abstract: LLM agents reach users through resellers, who may rebrand a developer's agent or substitute a cheaper model. When provenance is disputed, attribution rests on the trajectory log (the record of tool calls, observations, and execute…

  2. arXiv cs.AI TIER_1 English(EN) · Liming Zhu ·

    TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories

    LLM agents reach users through resellers, who may rebrand a developer's agent or substitute a cheaper model. When provenance is disputed, attribution rests on the trajectory log (the record of tool calls, observations, and executed actions, not the model's reasoning), which the r…