Preprint Open access
Understanding and Mitigating Token-Pruning-Induced Vulnerabilities in VLMs
Token-Pruning accelerates Vision-Language Models by removing redundant visual tokens, yet its safety implications remain underexplored. In this work, we present the first comprehensive safety evaluation of Token-Pruning mechanisms and find that: most pruning strategies significantly degrade safety as pruning ratios inc …