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cs.CV2025
TinyDrop: Tiny Model Guided Token Dropping for Vision Transformers
Guoxin Wang, Qingyuan Wang, Binhua Huang +2
Vision Transformers (ViTs) achieve strong performance in image classification but incur high computational costs from processing all image tokens. To reduce inference costs in larg…
cs.CV2025
Optimal Brain Connection: Towards Efficient Structural Pruning
Shaowu Chen, Wei Ma, Binhua Huang +5
Structural pruning has been widely studied for its effectiveness in compressing neural networks. However, existing methods often neglect the interconnections among parameters. To a…
cs.CV2025
ORXE: Orchestrating Experts for Dynamically Configurable Efficiency
Qingyuan Wang, Guoxin Wang, Barry Cardiff +1
This paper presents ORXE, a modular and adaptable framework for achieving real-time configurable efficiency in AI models. By leveraging a collection of pre-trained experts with div…