Sangin Lee

CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large Vision-Language Models

In large vision-language models (LVLMs), visual tokens typically constitute the majority of input tokens, leading to substantial computational overhead. To address this, recent studies have explored pruning redundant or less informative visual tokens for image understanding tasks. However, these met…