ID-Selection: Importance-Diversity Based Visual Token Selection for Efficient LVLM Inference
arXiv:2604.05601v1 Announce Type: new
Abstract: Recent advances have explored visual token pruning to accelerate the inference of large vision-language models (LVLMs). However, existing methods often struggle to balance token importance and diversity:…