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English(EN) RMCW: A Deletion-Robust Watermark Based on Reed--Muller Codes for Language Models

新的RMCW水印方法增强了LLM文本的鲁棒性

研究人员开发了一种用于大型语言模型生成文本的新水印方法,称为Reed-Muller Code Watermarking (RMCW)。该技术旨在更有效地抵御删除攻击,这类攻击会通过改变词元位置来破坏传统水印。RMCW利用Reed-Muller码和Reed-Solomon一致性测试来识别经过后处理的生成文本。在OPT-1.3B和Llama 3.1 8B-Instruct等模型上的实验表明,RMCW在抵御各种删除和重写攻击的同时,能有效保持可检测性。 AI

影响 增强了在复杂的操纵技术下检测AI生成文本的能力。

排序理由 该集群包含一篇详细介绍语言模型输出新水印方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的RMCW水印方法增强了LLM文本的鲁棒性

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该集群包含一篇详细介绍语言模型输出新水印方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Yi Wang, Baicheng Chen, Yu Wang, Jian Zhao, Yilei Chen, Tianxing He ·

    RMCW:一种基于Reed-Muller码的语言模型删除鲁棒水印

    arXiv:2610.02817v1 Announce Type: cross Abstract: Large Language Model (LLM) watermarking provides a lightweight mechanism for identifying text generated by a specific model, but its robustness remains fragile under post-processing attacks. Deletion attacks are particularly chall…