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Oct 12 · Monday
All papers Found 14 papers Another 262 papers do not have category tags yet and are not included in filtered results.
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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 Persist-3 序贯检验，从隐藏表示识别未见越狱源
Published Oct 7
Evaluated models Llama2-7B-chat , Qwen2.5-7B-Instruct , Gemma-2-9B-it and others4 Abstract Persist-3 用有限窗口检验攻击流是否超出已知越狱源，检出率低于全历史 SR-DKW，但决策只依赖最近观测。Persist-3 是一个有限记忆的序贯检测器，用来判断攻击表示流是否已经不能由任何一个已知越狱源解释。 。
提出危害窗口与区间指标，统一评测分解攻击和提示注入下的智能体滥用监视
Published Oct 5
Evaluated models Gemma 4 26B-A4B , Qwen3.6 27B , Qwen3.5 27B and others12 Abstract 统一智能体滥用监视框架，动作视角兼顾两类威胁但危害定位仍存瓶颈。
用分类后缀提升激活探针对分布外恶意输入的检测
Published Oct 2
Evaluated models Llama-3.1-8B , Qwen3.5-9B , Gemma-4-12B Abstract 作者称排序增益来自分类格式，低 FPR 精度来自点名准则。用户轮后的分类后缀，被作者用作激活探针的分布外检测干预：排序看格式，低 FPR 精度看是否点名恶意/良性。
提出 DART，用去噪表征转移检测多轮智能体攻击并注入提醒
Published Sep 30
Evaluated models Qwen3-8B , Qwen3-14B , Qwen3-32B and others6 用能量势垒信号检测扩散语言模型的越狱
Published Sep 25
Evaluated models LLaDA-8B-Instruct , LLaDA-1.5 , Dream-v0-Instruct-7B and others4 Abstract 能量势垒把 dLLM 越狱分成掩盖初始状态或中途越垒，三个 logit 信号据此互补检测。Bach 等提出用去噪能量景观解释 masked diffusion 语言模型上的越狱，并由此得到三个免训练检测信号。 。
提出移动 Agent 轨迹审计器 MATE，判断轨迹是否违反可编辑安全策略
Published Sep 19
Evaluated models MATE-0.5B , MATE-1.5B , MATE-3B Abstract MATE 用合成轨迹微调轻量审计器，在可编辑策略下判断移动智能体轨迹是否违规并给出解释。MATE 是面向移动 GUI 智能体的轻量策略条件轨迹审计器，在给定自然语言安全策略时判断轨迹是否违规并解释原因。
提出局部稀疏无监督安全检测，标记偏离安全分布的输入
Published Sep 17
Evaluated models qwen2-1.5b-instruct , ministral-8b-instruct , llama3-8b-instruct and others6 提出 HERALD，用跨层有害投影轨迹检测越狱提示
Published Sep 12
Evaluated models Llama-3.1-8B-Instruct , Mistral-7B-Instruct , OLMo2-7B-Instruct and others4 Abstract HPD 用跨层投影形状区分有害与良性提示。
提出 MOLE 基准，评测监控器对 AI 智能体内部威胁的检出能力
Published Sep 7
Evaluated models GPT-5.3 Chat , GPT-5.5 , GPT-4.1 and others15 Abstract MOLE 构建了智能体内部威胁检测基准，作者指出高漏检现状与推理痕迹的防御价值，并展示了监控策略优化空间。MOLE 是首个针对前沿 AI 实验室智能体内部威胁检测的开放基准，旨在评估在有限每日审查预算与日常研发业务背景下识别恶意账号的能力。 。
提出 Agent MechSuits，对多轮 CLI Agent 做步级检测与子空间转向
Published Jun 22
Evaluated models LLaMA-3.1-8B , Qwen-2.5-7B , Gemma-2-9B Abstract 白盒步级探针加稀疏转向可压低三模型恶意动作，同时提高生成崩溃率。Agent MechSuits 是面向多轮 CLI 智能体的白盒、步级表示防御，并配有可执行轨迹基准 MAS。
提出 D²-Monitor，按犹豫步数把难提示路由到更强探针
Published May 25
Evaluated models LLaDA-8B-Base , LLaDA-8B-Instruct , LLaDA-1.5-8B and others4 提出 Meerkat，聚类并搜索 Agent 轨迹库以定位跨轨迹安全违规
Published Apr 14
Evaluated models GPT-5.4 , GPT-5.4-mini , Qwen3.5-397B-A17B and others5 Abstract Meerkat 用聚类与智能体搜索定位跨轨迹违规，并在真实评测轨迹中找出脚手架泄题与奖励黑客。Meerkat 是事后审计方法，用来在智能体轨迹仓库里找出单条看不出、合在一起才违反自然语言安全属性的见证。
提出 NeuroFilter，用激活探针过滤智能体多轮隐私攻击
Published Jan 21
Evaluated models GPT-OSS 20B , Qwen 2.5 32B Instruct , Llama 3.3 70B and others8 Defenses arXiv 2505.23559 · May 29, 2025 提出 SafeScientist 四层监控，阻止科研智能体执行高风险或不伦理任务
Published May 29, 2025
Evaluated models GPT-4o , GPT-4.1 , GPT-3.5-turbo and others5 Abstract 四层监控加科研安全基准。SafeScientist 是带四层监控的科研智能体框架，并用 SciSafetyBench 评测科学场景中的任务安全。
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