Translation in progress Some entries still include text in the original language.
Oct 12 · Monday
Another 254 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.
用训练数据归因估计错误建议样本对涌现失准的贡献
Published Sep 30
Evaluated models OLMo 3 7B-SFT , Qwen 2.5 1.5B , Qwen 2.5 3B and others11 Abstract 错误建议对涌现失调的贡献不均匀，归因过滤可增减失调，且最有效的是模型自己的分数。EleutherAI 用训练数据归因考察错误建议微调中，哪些样本推动涌现失调。 。窄域有害数据上的微调会使模型在无关问题上也给出有害回答。
提出 TAME 框架，定位并验证驱动涌现失准的回复 token
Published Sep 15
Evaluated models Llama-3.2-1B-Instruct , Qwen2.5-1.5B Abstract 提出 TAME 框架在 token 粒度定位 EM 信号，掩码高归因 token 成功切断跨任务未对齐。
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