Author

Lan He

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Preprint Sep 2026

StepPrune: Adaptive Sequential Visual Token Selection across Multimodal Large Language Models

Visual prefixes account for a major portion of the per-layer computation in multimodal large language models (MLLMs), making visual-token pruning a direct approach to accelerating inference. Existing top-K methods typically evaluate tokens independently and apply a uniform budget to all inputs, overlooking both selecti...

Han-Sen Zhang, Lan He, Min Yao et al. · 0 citations

Jul 2026

PathSelect: Sequential Token Selection for Whole Slide Pathology

This work reformulate WSI token pruning as a sequential selection process, enabling the model to autonomously learn an optimal routing strategy rather than relying on static heuristics.

Jing-Zhi Chen, Lan He, Zehong Chen et al. · arXiv.org · 2 citations

Preprint Aug 2026

DiffPrune: differentiable information throttling for token pruning in vision-language models

DiffPrune is proposed, which gives token scores a direct meaning and implements an Information Throttler, which injects variance-preserving noise into visual tokens, where high-score tokens remain close to their original representations, while low-score tokens carry less original information.

Lan He, Min Yao, S. Young et al. · 1 citation · ⚡1