2 papers
cs.AR2026
Realizable N:M Sparse Transformer Inference via Search-Kernel Co-Design
Yiming Liu, Wenqi Lou, Zhiguang Wang +4
Vision Transformers (ViTs) achieve strong accuracy but incur high inference latency. Semi-structured N:M sparsity can reduce arithmetic cost, yet its theoretical savings often fail…
cs.LG2026
Window-Diffusion: Accelerating Diffusion Language Model Inference with Windowed Token Pruning and Caching
Fengrui Zuo, Zhiwei Ke, Yiming Liu +3
Diffusion language models (DLMs) generate text through iterative denoising, but inference requires full-sequence attention at every iteration, resulting in substantial redundant co…