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...