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Oct 12 · Monday
Another 305 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 RAIM,用交叉拟合堆叠聚合廉价评审检测幻觉
Published Sep 30
Evaluated models Llama , Qwen , Mistral and others10 Abstract 十个廉价评审的堆叠在可采纳区间接近 Sonnet,代价主要是一次域内校准。
构建法律引用幻觉基准 LePhantomCite 并评测智能体核验
Published Jun 19
Evaluated models gpt-5-2025-08-07 , Opus 4.8 , Gemini 2.5 Flash and others13 Abstract 引用幻觉未随代际持续下降。法律引用核验被做成基准:伪造引用的法院文书在增加,生成端的幻觉率也没有随模型代际持续下降。
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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