Author

Van-Tam Nguyen

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Jul 2026

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

This work introduces TORINO (TOken Reduction via Interpretable coNcept Overlap), a plug-and-play framework for adaptive visual token reduction in VLMs that requires no fine-tuning of the underlying model.

Riccardo Renzulli, Gabriele Spadaro, Shruthi Gowda et al. · arXiv.org · 0 citations