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cs.CV2025
Improving Adversarial Transferability in MLLMs via Dynamic Vision-Language Alignment Attack
Chenhe Gu, Jindong Gu, Andong Hua +1
Multimodal Large Language Models (MLLMs), built upon LLMs, have recently gained attention for their capabilities in image recognition and understanding. However, while MLLMs are vu…
cs.CV2023
Initialization Matters for Adversarial Transfer Learning
Andong Hua, Jindong Gu, Zhiyu Xue +3
With the prevalence of the Pretraining-Finetuning paradigm in transfer learning, the robustness of downstream tasks has become a critical concern. In this work, we delve into adver…