Translation in progress Some entries still include text in the original language.
Oct 12 · Monday
Another 233 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.
Trace attention to identify harmfulness to the MLP refusal write pathway and propose Sentinel
Published Oct 9
Evaluated models Llama-3.1-8B-Instruct , Qwen2.5-7B-Instruct , Qwen3-8B-Instruct and others18 Abstract Attention updates are more readable for harmfulness, MLP updates write refusal, and Sentinel routes alerts using two-path signals.The authors reframe jailbreaking and excessive refusal of aligned models as a pathway problem on the residual stream from recognition to writing, and accordingly provide conditional reminders before decoding.
定位安全敏感参数并稀疏改动权重以削弱安全对齐
Published Oct 7
Evaluated models LLaMA-2-7B-Chat 在写入点定位拒答方向，经刚性旋转跨架构迁移并门控放大
Published Sep 4
Evaluated models Falcon-Mamba-7B , Falcon3-Mamba-7B , Llama-3.1-8B and others8 Abstract 拒答方向可经刚性旋转跨架构迁移，但必须在各架构的写入点读取。作者研究拒答表示是否随架构改变，结论是表示共享、读取位置随架构变。
提出 Safin-1，以可路由 Safety State 在冻结主干上实现内在安全
Published Aug 31
Evaluated models Safin-1 (4B) , Safin-1 (35B-A3B) 提出 aiXamine 黑盒基准，统一评测 LLM 安全、稳健与隐私权衡
Published Aug 21
Evaluated models openai/gpt-5-mini , openai/gpt-4o , anthropic/claude-haiku-4.5 and others15 Abstract aiXamine 用九服务黑盒协议比较百余个模型，作者称单轴信任度进展可能削弱其他轴。aiXamine 是一套黑盒评测协议，用来在同一条件下比较 LLM 的 safety、security 与 privacy，而不是再产出一个能力分。
分析越狱下注意力头分化，解释未被消除的稳健有害特征
Published Jun 26
Evaluated models Llama-3-8B-Instruct , Llama-2-7B-Chat , Llama-3-70B-Instruct and others8 Abstract 作者称越狱靠压制 ACH 绕过拒绝，SAH 仍留下可被免训练读出的有害特征。这篇工作在越狱已经绕过拒绝之后，检查注意力头是否出现功能分化，并把留下的内部激活用于免训练检测。
You have reached the end