FOA-Attack aligns global and clustered local features via optimal transport with dynamic ensemble weighting to create targeted adversarial images that transfer to closed-source multimodal LLMs.
Improv- ing the transferability of targeted adversarial examples through object-based diverse input
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Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment
FOA-Attack aligns global and clustered local features via optimal transport with dynamic ensemble weighting to create targeted adversarial images that transfer to closed-source multimodal LLMs.