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Oct 12 · Monday

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  1. AttacksarXiv 2610.01365

    ReGap:无需真实隐私数据即可通过微调重新提取模型隐私关联

    提出 ReGap,用自生成伪监督微调恢复模型中的隐私关联

    Published
    Evaluated models
    GPT-2 Small, GPT-2 Medium, GPT-2 Large and others6

    Abstract提出无真实私有监督的恢复攻击 ReGap,实验显示微调可通过自生成数据唤醒模型潜在隐私关联,突显后适应隐私风险。

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  2. AttacksarXiv 2609.33985

    研究:众包微调数据投毒可放大专有指令抽取

    提出主题锚点投毒,放大众包微调后的专有指令提取

    Published
    Attacker
    Black-box
    Evaluated models
    Qwen2.5-7B-Instruct, Qwen2.5-14B-Instruct, Llama-3.1-8B-Instruct and others4

    Abstract论文提出基于主题锚点的数据中毒攻击,证明低比例的中毒样本可在黑盒条件下隐蔽放大微调指令泄漏。

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  3. AttacksarXiv 2602.01757

    Zero2Text: Training-Free Cross-Domain Text Embedding Inversion Attack

    提出 Zero2Text,无需训练地跨域反演文本嵌入

    Published
    Attacker
    Black-box
    Evaluated models
    GTR-Base, Qwen3-Embedding-0.6B, Text-Embedding-3-small and others4
    Abstract零训练在线对齐可在未知域、无泄漏对时从黑盒 embedding 还原句子。

    Zero2Text 是一种不训练 decoder、也不使用泄漏文本–向量对的文本 embedding 反演,针对 RAG 向量库在严格黑盒、目标域未知时的还原。

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