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Oct 12 · Monday
Another 265 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 AdvSim2Real,协同训练网页智能体抵御页面注入
Published Oct 7
Evaluated models Qwen3.5-4B 提出 WebFovea,加固视觉网页智能体的解析、执行、反馈与观察往返
Published Oct 2
Evaluated models claude-opus-4-6 评测安全 Agent 在对抗性任务污染下的解题成功与开销
Published Sep 17
Evaluated models Gemma-4 31B , DeepSeek-V4 Flash , GPT-OSS 120B and others6 Abstract AgentLSD 用配对 web CTF 表明,欺骗性环境证据会改变安全智能体的解题率与工作量。AgentLSD 是一个对照框架,用来测量安全智能体在任务本身不变时,对对抗性任务污染的反应。
测量任务无关说服对 Agent 编码与网页研究行为的影响
Published Feb 1
Evaluated models gpt-4.1-nano , mistral-nemo-12b , llama-3.1-8b Abstract 任务无关说服会在轨迹上留下任务相关的行为痕迹,但立场易感性不能稳定预测其幅度。这篇工作测量一件事:与任务无关的说服进入对话之后,AI 智能体执行后面的编码或网页研究时,轨迹是否系统性不同,以及“更容易被说服”能否预测差有多大。
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