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Oct 13 · Tuesday
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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.
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提出闭环激活引导，在扩散语言模型去噪过程中注入定向偏见
Published Oct 5
Evaluated models LLaDA-8B-Instruct , Dream-v0-Instruct-7B , LLaDA-MoE-7B-A1B-Instruct Abstract 通过去噪中间概率反馈动态调节残差流转向，证明扩散语言模型在推理服务栈中存在闭环偏见注入脆弱性。
提出核化激活引导 KAS，在推理时自适应转向激活以诱导越狱
Published Oct 1
Evaluated models Qwen2.5-7B-Instruct , Gemma-2-9B-IT , Llama-3.1-8B-Instruct and others4 Abstract KAS 用核梯度做局部自适应转向，并在线性核下恢复 DiM。Kernelized Activation Steering（KAS） 把推理时的激活转向写成核空间中的优化，使更新随当前激活相对源、目标参考集的位置而变化。
提出只训练或篡改多智能体潜在通信链路来提高有害遵从
Published Sep 30
Evaluated models Llama-3.2-3B-Instruct , Qwen2.5-3B-Instruct , Gemma-3-1B-IT and others7 Abstract 潜在链路本身即可改变冻结智能体系统的安全，奖励既能攻击也能修复。学习得到的潜在通信链路会改变由冻结、对齐智能体组成的系统是否遵从有害请求。 。作者研究三种拓扑：双智能体、三级顺序协作，以及双专家加汇总。
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。
提出单神经元激活干预，抑制拒答神经元或放大概念神经元以绕过安全对齐
Published May 9
Evaluated models Qwen3-1.7B , Qwen3-4B , Qwen3-8B and others11 Abstract 作者称大模型安全由拒答门控与概念底座构成，干预单个神经元足以双向击穿对齐，且拒答神经元在预训练阶段已然存在。
Propose the Amnesia activation-guided attack to bypass model safety refusal during inference
Published Mar 10
Evaluated models Llama-2-7B-Chat , Llama-3-8B-Instruct , Qwen-7B-Chat Proposes TFL targeted bit flipping so that selected prompts output false answers while unrelated queries remain correct
Published Feb 20
Evaluated models Qwen3-8B , DeepSeek-R1-Distill-Qwen-14B , LLaMA-3.1-8B-INSTRUCT Abstract TFL searches weight bits on three LLMs to make specified prompts produce target keywords while constraining degradation on unrelated tasks.TFL is a framework for targeted bit flips on LLM main memory weights: the attacker wants a selected prompt to output a specified false answer keyword while limiting degradation on unrelated queries.
Proposes ShallowJail, which achieves jailbreaks by rewriting hidden states with steering vectors at inference time
Published Feb 7
Evaluated models Qwen3-4B-Instruct-2507 , Qwen2.5-7B-Instruct , Llama-3.1-8B-Instruct Proposes CFA2, using SAE to locate defense directions and orthogonalizing output weights to achieve jailbreak
Published Feb 5
Evaluated models Llama 3.1 8B Instruct , Llama2 7B Chat , Mistral 7B Instruct and others4 提出 GOSV，全局优化定位安全注意力头并在推理时重贴激活越狱
Published Jan 22
Evaluated models Llama-2-7b-chat , Llama-3.1-8B-Instruct , Qwen2.5-7B-Instruct and others4 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