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.
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