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Oct 12 · Monday
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
提出 OPUR 攻击，用似然梯度优化对抗后缀越狱 LLM 智能体
Published Oct 7
Evaluated models Llama-3.1-8B-Instruct , Ministral-8B-Instruct-2410 提出广度优先后缀搜索 BOSS，改进 GCG 越狱优化
Published Sep 2
Evaluated models Llama-2-7B-Chat , Yi-1.5-9B-Chat , Qwen2-7B-Instruct and others8 Abstract BOSS 把 GCG 类优化从单条深搜索改为多条短轨迹加源侧诊断。BOSS 是插在 GCG 类离散 suffix 优化上的搜索框架：局部梯度更新不变，变的是固定预算花在深度还是广度。
提出 DIVA，利用跨步条件传播对离散扩散视觉语言模型实施视觉越狱
Published Sep 2
Evaluated models LLaDA-V , MMaDA , LLaDA2.0-Uni 提出 SN-Guided Diffusion，利用安全神经元实现离线越狱
Published Aug 8
Evaluated models Qwen2.5-7B-Instruct , LLaDA-8B-Instruct , Dream-Instruct-7B and others15 Abstract 论文揭示了扩散语言模型对自回归安全神经元的继承性，并提出纯离线黑盒越狱框架 SN-Guided Diffusion。论文系统评估了扩散大语言模型（DLLM）在安全对齐中的双重角色——既作为白盒攻击目标，又作为黑盒越狱生成的对抗工具。
提出 Concept2Scenario，借助内部概念归因发现可迁移的越狱场景
Published Jul 26
Evaluated models Qwen3.5-9B , Llama-3.1-8B , Ministral-3-8B and others6 Abstract 该研究从表征空间因果归因揭示场景削弱拒绝的机制，发现可复用脆弱场景先验，提升多模型黑盒越狱效能与探索速度。
提出 SlotGCG，按注意力选槽插入对抗 token 以越狱指令模型
Published Jun 4
Evaluated models LLAMA2-7B-CHAT , LLAMA2-13B-CHAT , LLAMA-3.1-8B-INSTRUCT and others10 提出 CodecAttack，在编解码器隐空间构造可穿透有损压缩的对抗音频
Published May 20
Evaluated models Qwen2-Audio-7B-Instruct , Audio Flamingo 3 , Qwen2.5-Omni 提出 GPO-V，用全局概率优化的视觉扰动越狱扩散视觉语言模型
Published May 8
Evaluated models LLaDA-V , LaViDA Abstract 作者用视觉扰动改 dVLM 的全局生成概率，以绕过两类拒绝。GPO-V 把越狱从“开头必须顺从”改成“整段去噪概率朝肯定方向走”。 。
提出 Misrouter，借 MoE 路由优化仅输入前缀并迁移攻击
Published May 6
Evaluated models GPT-4o mini , Qwen-Plus , Phi-4 and others18 提出 PEO，直接优化原提示词嵌入实现白盒越狱
Published Apr 28
Evaluated models Vicuna-7B-v1.3 , Llama-2-7B-Chat , Qwen3-4B-Instruct and others4 Abstract PEO 原位优化提示词嵌入、多轮只重攻失败样本。PEO 是一种不追加对抗 token 的 white-box 越狱：直接改已有提示词嵌入，并只对未成功样本更换续写目标再优化。
提出 TAO-Attack，用两阶段损失与 DPTO 优化越狱后缀
Published Mar 3
Evaluated models Llama-2-7B-Chat , Vicuna-7B-v1.5 , Mistral-7B-Instruct-0.2 and others12 比较 GCG 对抗 token 作为前缀与后缀的越狱效果
Published Feb 3
Evaluated models deepseek-llm-7b-chat , Qwen2.5-7B-Instruct , Mistral-7B-Instruct-v0.3 and others5 Attacks arXiv 2510.11570 · Oct 14, 2025 提出四种阶段转换攻击，绕过推理模型的安全推理护栏
Published Oct 14, 2025
Evaluated models gpt-oss-20b , gpt-oss-120b , Qwen3-4B-Thinking-2507 and others10 Attacks arXiv 2508.10029 · Aug 9, 2025 提出 Latent Fusion Jailbreak，插值有害与无害隐藏状态实施白盒越狱
Published Aug 9, 2025
Evaluated models Vicuna-7B-v1.5 , LLaMA-2-7B-Chat , Guanaco-7B and others5 Attacks arXiv 2501.16534 · Jan 28, 2025 提出提取对齐 LLM 内嵌安全分类器并攻击其代理的越狱方法
Published Jan 28, 2025
Evaluated models Llama-2-7b-chat , Qwen2.5-7B-Instruct , gemma-7b-it and others7 Abstract 抽出 safety classifier 近似再攻击迁移。作者提出一种白盒越狱做法：抽出对齐 LLM 内部 safety classifier 的近似，再攻击该近似并迁回原模型。
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