On Adversarial Vulnerability of Vision-Language Models through the Lens of Intermediate Spectral Subspaces

Chethan Krishnamurthy Ramanaik, Tobias Callies, Michael Hecht +1

Adversarial vulnerability in deep neural networks (DNNs) has been studied from the perspectives of decision-boundary geometry, feature robustness, input-output Jacobians, and the i…