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cs.LG2025
FastForward Pruning: Efficient LLM Pruning via Single-Step Reinforcement Learning
Xin Yuan, Siqi Li, Jiateng Wei +7
Pruning is an effective method for compressing Large Language Models, but finding an optimal, non-uniform layer-wise sparsity allocation remains a key challenge. While heuristic me…
cs.LG2024
AutoDFP: Automatic Data-Free Pruning via Channel Similarity Reconstruction
Siqi Li, Jun Chen, Jingyang Xiang +2
Structured pruning methods are developed to bridge the gap between the massive scale of neural networks and the limited hardware resources. Most current structured pruning methods…
cs.LG2023
SUBP: Soft Uniform Block Pruning for 1xN Sparse CNNs Multithreading Acceleration
Jingyang Xiang, Siqi Li, Jun Chen +4
The study of sparsity in Convolutional Neural Networks (CNNs) has become widespread to compress and accelerate models in environments with limited resources. By constraining N cons…