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Oct 13 · Tuesday
Another 215 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.
用 SCM 合成会话并训练检测器识别推理层滥用
Published Sep 29
Evaluated models gradient-boosted detector (GBDT/XGBoost) 提出 SafeEvolve,用轨迹证据协同演化安全 harness 与策略
Published Sep 3
Evaluated models Qwen3.5-4B , Qwen3-4B-Instruct-2507 , Qwen3.5-1.7B and others4 Abstract SafeEvolve 用轨迹证据协同更新安全 harness 和策略,在两个 4B 模型的智能体安全基准上改变安全与效用。SafeEvolve 把已完成的 on-policy 轨迹变成安全 harness 的有界更新,并用两阶段 SFT-RL 把这些更新内化进工具使用策略。
提出 CodeSpear 越狱,借语法约束解码生成恶意代码,并给出 CodeShield 防御
Published Jun 10
Evaluated models Qwen2.5-Coder-7B , Qwen2.5-Coder-32B , Qwen2.5-7B and others10 Abstract 论文发现语法约束解码会破坏自然语言安全对齐,提出 CodeSpear 越狱攻击与基于蜜罐代码对齐的 CodeShield 防御。
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