Liaoyuan Feng

Robustifying Zero-Shot Vision Language Models by Subspaces Alignment

Vision-Language Models (VLMs) enjoy strong zero-shot performance but are vulnerable to adversarial attacks posing security risks. Adversarially robust fine-tuning enhances zero-shot robustness on new datasets while preserving the natural performance of pre-trained VLMs. However, prior methods use sa…