What Makes VLMs Robust? Towards Reconciling Robustness and Accuracy in Vision-Language Models
arXiv:2603.12799v2 Announce Type: replace
Abstract: Achieving adversarial robustness in Vision-Language Models (VLMs) inevitably compromises accuracy on clean data, presenting a long-standing and challenging trade-off. In this work, we revisit this tr…