Chunzhao Xie

DCP: Dual-Cue Pruning for Efficient Large Vision-Language Models

Large Vision-Language Models (LVLMs) achieve remarkable performance in multimodal tasks but suffer from high computational costs due to the large number of visual tokens. Existing pruning methods either apply after visual tokens enter the LLM or perform pre-pruning based solely on visual attention.