2 papers
cs.CV2026
Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective
Zhenfeng Su, Kang Zhao, Han Bao +4
While prior studies have successfully compressed vision Transformers (ViTs) through various pruning techniques, most have concentrated on width pruning to achieve significant reduc…
cs.LG2025
Beyond 2:4: exploring V:N:M sparsity for efficient transformer inference on GPUs
Kang Zhao, Tao Yuan, Han Bao +6
To date, 2:4 sparsity has stood as the only sparse pattern that can be accelerated using sparse tensor cores on GPUs. In practice, 2:4 sparsity often possesses low actual speedups…