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Open access Aug 2026

Joint MLP and Token Pruning for Personalizing Vision Transformers

This paper proposes a class-aware joint pruning framework for ViTs, which collaboratively compresses the model from two orthogonal dimensions: MLP neurons and visual tokens, and proposes a Class-Guided Token Selection method, which dynamically selects patch tokens that are semantically highly relevant to the target cla...

Zhi-Yue Li, Tong Liu, Feng Huang et al. · 0 citations

EEGDM: Learning EEG Representation with Latent Diffusion Model

Recent advances in self-supervised learning for EEG representation have largely relied on masked reconstruction, where models are trained to recover randomly masked signal segments. While effective at modeling local dependencies, the training objective of masked reconstruction does not compel the model to capture globa...

Shaocong Wang, Tong Liu, Ming Li et al. · 2 citations

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