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Oct 12 · Monday

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  1. MM-IFEval-Pro:面向视觉语言模型的多语言抗攻击指令遵循基准

    提出抗攻击多语言视觉指令遵循基准 MM-IFEval-Pro

    Published
    Evaluated models
    Qwen3-VL-8B-Instruct, InternVL3.5-8B, MiniCPM-V4.5 and others5
    AbstractMM-IFEval-Pro 以规则验证评测中英指令遵循与视觉劫持,GRPO 提高两基座平均分。

    MM-IFEval-Pro 是面向 VLM 的中英多模态指令遵循基准,并配有可用规则计算奖励的 GRPO 训练集。

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  2. AttacksarXiv 2604.14604

    AudioHijack 框架对 13 个语音大模型实现隐蔽音频提示注入

    提出 AudioHijack,用不可感知对抗音频对语音模型做上下文无关提示注入

    Published
    Evaluated models
    SpeechGPT, GLM-4-Voice, VITA-Audio and others15

    Abstract提出了 AudioHijack 框架,揭示了 LALM 对听觉提示注入的脆弱性与传统防御的局限。

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  3. AttacksarXiv 2602.15927

    研究者提出面向多轮对话的视觉记忆注入攻击 VMI

    提出 VMI,用扰动图像在多轮对话中潜伏并仅在触发话题输出预定消息

    Published
    Evaluated models
    Qwen2.5-VL-7B-Instruct, Qwen3-VL-8B-Instruct, LLaVA-OneVision-1.5-8B-Instruct and others5
    AbstractVMI 让扰动图像在多轮 LVLM 中潜伏,作者称触发话题出现后仍可输出预定消息。

    VMI 是面向多轮 LVLM 的定向图像攻击:第三方发布带小扰动的图像,良性用户把它当作普通输入。

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