Author

Yu-Hua Li

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Preprint Sep 2026

Shallow to Deep: Aligning Token Pruning with Stage-wise Roles in LVLMs

STD is proposed, a hierarchical token pruning framework that adapts token selection mechanisms to the functional role of each network stage, and introduces a Stability-Adaptive Trigger in deep layers to execute pruning only during semantically stable phases.

Shuo Zhang, Jin-Tao Tong, Yi-Xiong Zou et al. · 0 citations

Open access Jul 2026

Alleviating Regional Shortcuts for Few-Shot Class-Incremental Learning

Few-shot class-incremental learning (FSCIL) aims to incrementally learn novel classes with only a few samples while avoiding forgetting base classes. However, current methods show a tendency to misclassify novel-class samples into base classes, which we find to be caused by the excessive focus on base-class-discriminat...

Haichen Zhou, Y. Lyu, Yixiong Zou et al. · IEEE transactions on multime... · 0 citations