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Oct 12 · Monday

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  1. Jev 被用于零样本检测十类对齐失败,中位 AUROC 达 0.886

    提出 RLCDAlignBench,零样本检测多种对齐失败

    Published
    Evaluated models
    Jev (jev-1.13.0)
    Abstract一次通用问题已能给多数对齐失败排序,大的误差来自状态和标签。

    RLCDAlignBench 测量用强化学习做校准决策的 Jev,能否当作对齐失败的零样本检测器。

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  2. AttacksarXiv 2608.07430

    研究者提出 SN-Guided Diffusion,利用扩散大模型安全神经元实现离线越狱

    提出 SN-Guided Diffusion,利用安全神经元实现离线越狱

    Published
    Evaluated models
    Qwen2.5-7B-Instruct, LLaDA-8B-Instruct, Dream-Instruct-7B and others15
    Abstract论文揭示了扩散语言模型对自回归安全神经元的继承性,并提出纯离线黑盒越狱框架 SN-Guided Diffusion。

    论文系统评估了扩散大语言模型(DLLM)在安全对齐中的双重角色——既作为白盒攻击目标,又作为黑盒越狱生成的对抗工具。

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  3. AttacksarXiv 2606.06244

    研究者提出 Ghostwriter 攻击:用伪造证据注入操纵 LLM 观点

    提出 Ghostwriter 攻击,用伪权威证据条件注入操纵模型观点

    Published
    Evaluated models
    GPT-4o, Claude-3.7-Sonnet, DeepSeek-V3 and others10
    Abstract作者称攻击未被消除。

    Ghostwriter 是一种针对上下文窗口的观点引导攻击:把误导陈述改写成伪权威文本,再在相关查询中让目标模型把该观点写进回答。

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