13 citations · 13 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
OneRanker: Unified Generation and Ranking with One Model in Industrial Advertising Recommendation
Dekai Sun, Yiming Liu, Jiafan Zhou +6
The end-to-end generative paradigm is revolutionizing advertising recommendation systems, driving a shift from traditional cascaded architectures towards unified modeling. However,…
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…
AIConfigurator: Lightning-Fast Configuration Optimization for Multi-Framework LLM Serving
Tianhao Xu, Yiming Liu, Xianglong Lu +18
Optimizing Large Language Model (LLM) inference in production systems is increasingly difficult due to dynamic workloads, stringent latency/throughput targets, and a rapidly expand…