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Oct 12 · Monday
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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。
提出红蓝对抗评测平台 ACEA，分开计量攻击强度与防御效果
Published Sep 8
Evaluated models openai/gpt-4o , google/gemini-2.5-pro , google/gemma-3-27b-it and others5 Abstract ACEA 用 ASAP 让红蓝对同一目标对打。ACEA 是让可插拔红队和蓝队共享一个目标 LLM 的对打场地，把攻击强度和防御效果分开记分。作者要补三处空缺：双方只能对着固定对手分开练。LLM judge 分不清真实泄露和幻觉，拦截后又看不到攻击有多强。
提出 CompoSkill，将逐个通过扫描的技能编排为攻击链
Published Aug 17
Evaluated models GPT-5.4 , Gemini-3.1-flash , DeepSeek-V4 and others4 Abstract 论文分析了智能体技能组合风险，指出单包安全认证状态不具备可组合性，需转向路径级防护。
提出 SkillVetBench 评估开源 Agent 技能的多维安全风险
Published Jun 15
Evaluated models Qwen2.5-14B-Instruct , Qwen2.5-32B , Llama-3.1-70B and others6 Abstract 公开排行榜用 LLM-as-Judge 给技能分列 SARS 与 CVSS，并对照市场官方审查。
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