TORINO: Token Reduction via Interpretable Concept Overlap in Vision-Language Models.

arXiv:2607.04593v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have demonstrated impressive capabilities across different tasks, but their computational cost is dominated by the large number of visual tokens fed to the language model.