TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning
arXiv:2609.37581v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visual tokens. Recent visual token pruning methods…
Read the full story at arXiv cs.AI ↗
ImpactNotable 31/100
Why it mattersRule-based estimate: event keywords (+4); trust 6/10.
RegionsGlobal
Published1 h ago (Wed, 30 Sep 2026 04:00:00 GMT)
RetrievedWed, 30 Sep 2026 04:00:56 GMT via rss
ClassifiedWed, 30 Sep 2026 04:01:19 GMT by heuristic
AuthorJing Wang, Zhiping Wu, Dongdong Ren, Youfang Han, Wei Zhao, Wenbin Li