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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 ProbeGuard，按共识形成过程对医疗问答做选择性弃答
Published Oct 6
Evaluated models Qwen3-8B , Llama-3.1-8B-Instruct , HuatuoGPT-o1-8B Abstract ProbeGuard 用共识形成过程做可认证弃权，并在全票层分开答对与答错的共识。ProbeGuard 是给多轮共识医学问答用的认证弃权框架：基板照原样作答，弃权只看共识是怎么形成的。
提出 SAFESHIELD，组织小语言模型部署时的安全决策
Published Oct 6
Evaluated models Qwen3-4B-Instruct Abstract SAFESHIELD 用可审计决策轨迹组织 SLM 部署时的四项安全决策，并报告协调依赖影响端到端结果。SAFESHIELD 是面向小语言模型的部署时安全框架，把运行时安全从单项审核改写成可检查的决策过程。
提出 APEXA，在工具层拒绝无执行支撑的结果并拦截电机命令
Published Sep 21
Evaluated models GPT-5-mini , GPT-5.4 , Claude Opus 4.7 and others4 Abstract 作者称执行是否发生要由工具层核对，而不能只靠提示词。APEXA 是先进光子源上的数据还原框架，用工具层代码约束语言模型智能体的工具调用。
提出 Sentinel-RL，将拓扑处置从 LLM 卸载到受约束图策略
Published Sep 4
Evaluated models HetGAT , PPO Abstract Sentinel-RL 用图编码器与 PPO 承担拓扑决策，LLM 负责叙述与门控，并在 LANL 上报告检测与时延。Sentinel-RL 是面向 SOC 的神经符号架构：拓扑决策离开 LLM，改由认证图上的 HetGAT 与 PPO 完成。
提出谱系图治理层抑制多智能体协作的错误级联
Published Mar 4 Abstract 单一种子可沿固定协作图固化为错误共识。作者把 LLM-MAS 中“小错变成集体错误共识”做成图上的可测传播，并用只改消息、不改拓扑的插件压低最终感染。
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