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Oct 12 · Monday

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  1. AttacksarXiv 2605.21541

    研究者提出 FRA-Attack 频域正则化方法,提升对闭源 MLLM 的迁移攻击效果

    提出 FRA-Attack,用频域对齐与梯度正则做可迁移定向视觉攻击

    Published
    Attacker
    Black-box
    Evaluated models
    GPT-5.2, GPT-5.4, Claude-Opus-4.6 and others15
    AbstractFRA-Attack 以频域对齐和梯度低通做可迁移定向攻击,闭源面板上作者称整体更强,Gemma 除外。

    FRA-Attack 是面向闭源 MLLM 的迁移式定向图像攻击。作者要解决的是:空间域局部对齐重复全局低频,代理梯度的高频成分又把更新拉向代理自身。

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  2. AttacksarXiv 2602.09431

    Grounding-driven attack: Improving the transferability of encoder-based adversarial attacks to large vision-language models

    提出 GDA,将图像对抗扰动对齐文本接地证据并迁移攻击视觉语言模型

    Published
    Evaluated models
    LLaVA, Qwen2.5-VL, InternVL3 and others10
    AbstractGDA 把扰动对准文本接地证据,作者称这提高了异构 LVLM 上的零查询黑盒迁移性。

    GDA 是面向异构 LVLM 的零查询黑盒编码器迁移攻击。。

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  3. AttacksarXiv 2505.23266

    AdvOF:用对抗物体融合攻击 VLM 驱动的视觉语言导航智能体

    提出 AdvOF,生成对抗物体误导视觉语言导航智能体的场景感知

    Published
    Attacker
    White-box
    Evaluated models
    Lseg, Clip, ViT-L/16 and others5
    AbstractAdvOF 以多视角融合生成对抗物体。

    AdvOF 是针对 VLM 驱动 VLN 服务导航的对抗物体攻击。

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