Yuxiang Duan

TransPrune: Token Transition Pruning for Efficient Large Vision-Language Model

Large Vision-Language Models (LVLMs) have advanced multimodal learning but face high computational cost issues due to the input of large number of visual tokens, motivating token pruning to improve inference efficiency.The key challenge lies in identifying which tokens are truly important.Most exist