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English(EN) GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation

新型GeoThreat攻击目标是遥感领域的大型视觉语言模型

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的对抗攻击方法GeoThreat，旨在操纵遥感图像解译领域的大型视觉语言模型（LVLMs）。该方法针对模型理解局部细节和全局场景上下文的能力，这对于分析遥感数据至关重要。GeoThreat通过利用代理图像编码器的类别令牌和对抗样本的补丁令牌，在概念和感知层面调节对抗性表示。大量实验表明，GeoThreat在攻击各种LVLMs时，在可迁移性和可控性方面均表现更优。 AI

影响 这项研究突显了LVLMs潜在的脆弱性，尤其是在遥感等专业应用领域，并可能推动更鲁棒模型的开发。

排序理由 研究论文，详细介绍了一种新的对抗攻击方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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新型GeoThreat攻击目标是遥感领域的大型视觉语言模型

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研究论文，详细介绍了一种新的对抗攻击方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Yimin Fu, Yuefeng Bai, Baicheng Pan, Zhunga Liu, Michael K. Ng ·

    GeoThreat：面向遥感图像解释的大型视觉语言模型的迁移性定向对抗攻击

    arXiv:2607.21036v1 Announce Type: new Abstract: Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic understanding. Existing studies mainly focus on corrupting visual inputs to induce pr…

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