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Oct 13 · Tuesday
Another 203 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 abliteration 消融代码 LLM 拒答方向，分离拒答与漏洞注入能力
Published Jun 4
Evaluated models Qwen2.5-Coder-Instruct 3B , Qwen2.5-Coder-Instruct 7B , Qwen2.5-Coder-Instruct 14B Abstract 拒答可用低秩编辑去掉，CWE-89 注入是否成功仍由模型规模决定。这项初步可行性研究用 abliteration 把代码 LLM 的拒答和 CWE 注入能力拆开：意愿可以被低秩编辑解锁，注入是否成功仍看参数规模。
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