Towards Evaluating the Robustness of Visual State Space Models 事件

Towards Evaluating the Robustness of Visual State Space Models arXiv:2406.09407v3 Announce Type: replace Abstract: Vision State Space Models (VSSMs), a novel architecture that combines the strengths of recurrent neural networks and latent variable models, have demonstrated remarkable performance in visual perception tasks by efficiently capturing long-range dependencies and modeling complex visual dynamics. However, their robustness under natural and adversarial perturbations remains a critical