AI RESEARCH
Towards Evaluating the Robustness of Visual State Space Models
arXiv CS.CV
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ArXi:2406.09407v3 Announce Type: replace Vision State Space Models (VSSMs), a novel architecture that combines the strengths of recurrent neural networks and latent variable models, have nstrated 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 concern.