EvoCut: Multi-Layer Evolution-Aware Visual Token Compression for Efficient Large Vision-Language Models 事件

EvoCut: Multi-Layer Evolution-Aware Visual Token Compression for Efficient Large Vision-Language Models arXiv:2606.01756v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong performance on image and video understanding tasks, but their inference efficiency is constrained by the large number of visual tokens produced by vision encoders. Most existing visual token compression methods estimate token importance from attention scores or representation properties at spec