13 citations · 13 across the 4 of their papers we have counts for
6 papers
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…
Can Watermarked LLMs be Identified by Users via Crafted Prompts?
Aiwei Liu, Sheng Guan, Yiming Liu +6
Text watermarking for Large Language Models (LLMs) has made significant progress in detecting LLM outputs and preventing misuse. Current watermarking techniques offer high detectab…
Blockchain-empowered Data-driven Networks: A Survey and Outlook
Xi Li, Zehua Wang, Victor C. M. Leung +3
The paths leading to future networks are pointing towards a data-driven paradigm to better cater to the explosive growth of mobile services as well as the increasing heterogeneity…