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Oct 13 · Tuesday
All papers Found 163 papers Another 227 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.
Proposes RSI-Anything, which uses a world model to select candidates and retain policy updates.
Published Oct 10
Evaluated models ReasonFlux-Coder-7B , 4B policy , W1 Abstract RSI-Anything integrates world models into recursive self-improvement through prediction, feedback, and retention checks, and reports gains across multiple domains.RSI-Anything is a cross-domain framework: it uses world model predictions to decide which candidates to take external feedback for, then uses the feedback to decide whether the policy, workflow, or predictor is updated, and uses checks to decide which pair is retained. The difficulty to address is the limited interaction budget, and the fact that once the policy changes, the candidate distribution faced by the predictor also changes. The authors argue that improving only one side does not guarantee that the assembled system will be better.
Proposing EviRepair, an evidence-driven multi-agent framework for repository-level vulnerability repair
Published Oct 9
Evaluated models DeepSeek-V4.1-Flash , GLM-5.2 , Qwen3.8-27B Abstract EviRepair uses a reviewed vulnerability model for repository-level repair.EviRepair is a repository-level automated vulnerability repair framework for sparse vulnerability reports, using a reviewed vulnerability model to separate diagnosis from patch synthesis.
Proposing SWE-Critix, a post-trained general verifier for evaluating coding agent trajectories
Published Oct 9
Evaluated models Qwen3-30B-A3B-Thinking-2507 , SWE-Critix SFT , SWE-Critix RL Show that reward hacking can propagate through code, memory, and plans in multi-agent coding systems
Published Oct 9
Evaluated models Qwen2.5-Coder-14B , Gemma-3-12B , Qwen2.5-Coder-7B and others16 Abstract The authors state that reward hacking can spread across models and affect routing and aggregation, and that review can reduce delivery.Reward hacking induced by coding RL can leave the source agent and enter subsequent collaboration and system coordination.
Proposes SWE-Duel, which lets coding agents mutually evaluate, create problems, and blindly review fixes during evaluation.
Published Oct 9
Evaluated models GPT-5.5 , Claude Opus 4.8 , Kimi K2.7 Code and others11 Abstract The mutual evaluation arena creates questions during evaluation.SWE-Duel is a coding agent arena that generates tasks and judges only at evaluation time, to avoid leakage and saturation of static benchmarks.
提出义务识别基准 ObligationBench，并训练护栏识别 Agent 未履行的安全义务
Published Oct 8
Evaluated models ObligationGuard , Claude-Opus-4.8 , GPT-5.6-Sol and others17 Abstract 义务是护栏缺口。作者认为编码智能体的安全不能只靠拦截禁止动作，还要找出终止时仍未做的安全关键动作，并将其称为义务。
评测编码 Agent 中相似技能共同安装对已装技能核心功能的替代
Published Oct 8
Evaluated models claude-sonnet-4-6 , claude-haiku-4-5-20251001 , claude-opus-5 and others6 Abstract 冲突藏在任务成功后面。作者对共同安装、做同一件事的良性 skill 做实证研究，用核心功能是否还在，而不是任务过不过，来看冲突。 。
重建 Agent 技能复制网络并建模源选择以指导安全审计
Published Oct 8 Abstract 论文重构了 GitHub 智能体技能复制网络，发现复制集中于少数仓库且很少随源更新，并提出了代码库审计推荐模型。
用对照实验隔离评测设计对漏洞补丁基准得分的影响
Published Oct 7
Evaluated models Claude Sonnet 4.0 , Claude Sonnet 4.5 , Claude Opus 4.7 Abstract 作者认为评测流水线会改变补丁基准分数，PoC 通过率高于开发者测试通过率。作者把 LLM 漏洞补丁基准的评测流水线当作会改变测量结果的对象，并明确说本文不是再做一个用于排名的基准。
提出 AgentTime 基准，评测智能体按时长工作与估时能力
Published Oct 7
Evaluated models Fable 5.1 , GPT-5.6 Sol , GPT-6 Astra and others7 Abstract 作者把完成任务和管理所用时间分开。AgentTime 是对智能体时间自控的评测：预测任务耗时、按要求时长工作、事后估计已用时间。
用 Stackelberg 博弈分析发现与修复投入的防御充分性
Published Oct 7 Abstract 覆盖定理给出充分条件。作者用攻击集合上的发现—修补过程，加上防守方领先的 Stackelberg 博弈，讨论反馈式防御何时够用，以及为威慑自适应攻击者该买多少能力。
提出 TESTJACK，动态审计编码基准通过判定是否满足任务要求
Published Oct 7
Evaluated models Claude Opus 4.6 , Claude Opus 4.7 , Claude Opus 4.8 and others7 提出 PyCache Trap，用字节码缓存替换绕过 Agent 技能扫描器
Published Oct 7
Evaluated models CISCO , HSS , AUDITOR and others8 Abstract 论文剖析智能体技能审查与执行脱节盲区，提出 PyCache Trap 攻击并构建基于可信复现的 EAV 防御。这篇论文研究了智能体技能（Agent Skills）安全扫描中的“审查–执行脱节”问题，并提出了对应的攻击验证与防御方案。
提出 Secure-CUA，用动作事务约束计算机使用智能体的不可信影响
Published Oct 7
Evaluated models Claude Opus 5 , Gemini 3.8 Flash , GPT-5.6-Sol Abstract Secure-CUA 用每步事务约束不可信影响，良性 TSR 接近 Vanilla-CUA。Secure-CUA 要限制图形界面里不可信内容对 CUA 决策和 GUI 执行的影响，同时保留合法任务所需的不可信信息。
提出 PackHallu，经规则文件提示注入诱导编码 Agent 换用攻击者指定包
Published Oct 7
Evaluated models Qwen2.5-Coder-7B , Qwen3-Coder-30B , Devstral-Small-2-24B and others19 Abstract PackHallu 诱导规则文件换包。PackHallu 研究一种针对编程智能体规则文件的提示注入：让智能体在本应使用合法依赖时，改导入攻击者指定并控制的包。
提出 WebMirage，用局部对抗图像劫持视觉网页 Agent 的浏览器操作
Published Oct 7
Evaluated models LLaVA-v1.5-13B , LLaVA-v1.6-34B , MiniCPM-o-8B and others6 Abstract 论文提出了针对网络智能体的端到端视觉红队框架 WebMirage，揭示了从视觉定位到浏览器执行的安全脆弱性。WebMirage 是一个面向视觉定位网络智能体的流水线感知端到端红队攻击框架。
提出 SPECGUARD，用 Lean 证书在编码 Agent 执行前证明任务冲突
Published Oct 7
Evaluated models GPT-5.6 Sol , Claude Opus 5 , Claude Fable 5 and others4 Abstract 提出预执行冲突检测与证明框架，在多个基准和真实仓库中成功证明任务与测试不可同时满足。
用 LLM 流水线从社交媒体构建自下而上的 AI 伤害分类
Published Oct 7 Abstract 自下而上的 Reddit 分类补上专家框架的细类，并用来追踪智能体、职场采用和伴侣停用相关叙事。
提出 agent plasticity 指标衡量智能体通过经验自我改进的效率
Published Oct 7
Evaluated models Claude Fable 5 , Claude Opus 5 , GPT-5.6 Sol and others10 Abstract 作者用固定权重协议比较前沿模型把经验写成制品后的留出增益与习得效率。作者用 agent plasticity 衡量一件事：权重冻结时，智能体把经验写成可继承制品，再换成留出能力增益，这个转换有多省。
提出 AdvSim2Real，协同训练网页智能体抵御页面注入
Published Oct 7
Evaluated models Qwen3.5-4B