arXiv AI July 22, 2026 By Sibo Wang, Jie Zhang, Shiguang Shan, Xilin Chen, Wen Gao

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model

arXiv:2607. 18958v1 Announce Type: cross Abstract: While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulnerable to adversarial attacks, posing significant security risks.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model

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