Flexible Targeted Adversarial Alignment with Frequency-based Visual Focus for Attacking Large Vision-Language Models.
Although Large Vision-Language Models (LVLMs) have shown great capabilities across various downstream tasks, they are proven to be vulnerable to adversarial examples, thus resulting in critical safety issues. Existing adversarial attacks against LVLMs predominantly rely on uniform, image-wise perturbations, while large...