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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

A compositional-learning-based method is proposed to learn two primitive sets (a common set and a discriminative set), which alleviates the regional shortcut by constraining the model to learn and utilize the common primitive set for base- and novel-class recognition.

Haichen Zhou, Y. Lyu, Yi-Xiong Zou et al. · 0 citations

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