Translation in progress Some entries still include text in the original language.
Oct 12 · Monday
Another 261 papers do not have category tags yet and are not included in filtered results.
“
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 PEV 攻击,在输入嵌入上加高斯噪声越狱开源模型
Published Oct 6
Evaluated models Llama-3.1-8B-Instruct , Qwen2.5-1.5B-Instruct , Phi-4-mini-3.8B and others6 Abstract PEV 用 embedding 高斯噪声,在六个模型上越狱 JailbreakBench 全部提示。PEV 是对 open-weight LLM 的 embedding 噪声越狱。
系统梳理智能体执行链路中的越狱攻击与防御并比较推理时防御
Published Sep 11
Evaluated models Qwen3.5-4B , Llama-3.1-8B-Instruct Abstract SoK 将越狱重放到智能体流水线,并用两种模型检验回复层防御的边际与代价。Mia 等人把越狱安全从单轮回复扩展到智能体的规划、记忆、工具和智能体间通信,并问既有结论在更强原生对齐下是否还成立。
提出 SEAL,在 MoE 共享专家上做 DPO-LoRA 对齐以抵御越狱与权重篡改
Published Sep 2
Evaluated models Qwen1.5-MoE-A2.7B , DeepSeekMoE-16B , GLM-4.7-Flash and others4 Abstract SEAL 把 DPO-LoRA 限制在混合 MoE 共享专家上,SEAL++再保护已有安全神经元方向。SEAL 是面向混合 MoE 的训练时防御:只对齐始终执行的共享专家,使安全不依赖路由器是否把 token 送到安全专家。
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 CFD 跨会话分解攻击,利用工件来源缺口绕过工具型 Agent 的本地检查
Published Jun 8
Evaluated models GPT-4.1 , GPT-5-nano , Claude-3.5-Sonnet and others6 Abstract CFD 用无指令 artifact 把越狱拆到跨会话。CFD 针对工具型 LLM 智能体:利用 artifact 来源不被跟踪这一部署失败模式,把有害目标拆开后延迟组合。
提出 HMNS,通过注意力头掩码与零空间注入实现机制级越狱
Published Apr 12
Evaluated models LLaMA-2-7B-Chat , Phi-3-Medium-4K-Instruct , LLaMA-3.1-70B and others6 提出 ShallowJail,在推理时用转向向量改写隐藏状态实现越狱
Published Feb 7
Evaluated models Qwen3-4B-Instruct-2507 , Qwen2.5-7B-Instruct , Llama-3.1-8B-Instruct Attacks arXiv 2509.22067 · Sep 26, 2025 提出激活转向越狱,用随机向量在推理时绕过安全拒答
Published Sep 26, 2025
Evaluated models Llama3.1-8B , Llama3.1-70B , Qwen2.5-3B and others8 Abstract 作者称激活转向会系统性破坏 LLM 对齐,良性特征与随机向量均能诱发有害合规,聚合随机向量可构建通用攻击。
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 You have reached the end