Intaek Shin

Don't Ask the LLM: Visual Token Pruning with Spectral Structure and Semantic Relevance

Large vision-language models (LVLMs) represent images and videos as long visual-token sequences, substantially increasing inference costs. These costs motivate visual-token pruning, whose effectiveness depends on both what signal is used for selection and when that signal becomes available. Our analysis reveals complem...