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Oct 12 · Monday

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  1. 研究用消融移除代码 LLM 拒答方向,分离拒答与生成能力

    用 abliteration 消融代码 LLM 拒答方向,分离拒答与漏洞注入能力

    Published
    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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  2. 研究复现五个前沿模型的包名幻觉:跨模型共同幻觉 127 个包名,53 个仍可被注册

    复评前沿模型代码生成中的包名幻觉与抢注攻击面

    Published
    Evaluated models
    Claude Sonnet 4.6, Claude Haiku 4.5, GPT-5.4-mini and others5

    Abstract评估显示前沿模型包幻觉率收窄但威胁仍在,作者识别出跨模型通用攻击面并呼吁联合防御。

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