English(EN) $M^3$: A Multi-LLM System for Multi-Turn Jailbreaking as a Markov Decision Process

$M^3$框架使用马尔可夫决策过程进行高级LLM越狱

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 04:00

研究人员开发了一个名为$M^3$的新框架，该框架将大型语言模型的多轮越狱视为一个马尔可夫决策过程。这种方法旨在通过允许攻击LLM与目标LLM进行交互，并由单独的状态LLM的内部状态指导，来提高红队测试的有效性。在两个基准和六个目标模型上的评估中，$M^3$证明了比现有方法更高的攻击成功率，在ASR@5上取得了高达53%的提升。 AI

影响这项研究引入了一个新颖的、有原则的框架，通过系统地探索多轮越狱漏洞来评估和改进LLM安全性。

排序理由该集群包含一篇详细介绍LLM安全评估新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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Signal score: 12 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇详细介绍LLM安全评估新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yuqing Huang, Jack Ji, Jithin Pradeep, Sagarika Suresh, Jekaterina Novikova · 2026-10-26 04:00

$M^3$：一种将多轮越狱视为马尔可夫决策过程的多LLM系统

arXiv:2610.31937v1 Announce Type: new Abstract: Modern Large Language Models (LLMs) remain vulnerable to carefully orchestrated multi-turn interactions that progressively bypass safety mechanisms. However, many existing red-teaming approaches rely on heuristics or impose strong a…

本文如何被排名

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$M^3$：一种将多轮越狱视为马尔可夫决策过程的多LLM系统

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