2 papers
cs.DC2026
DScale: Scaling Block-Diffusion Speculative Decoding with Adaptive Verification
Rongjian Chen, Minxian Xu, Zhengxin Fang +2
Growing large language model applications demand efficient inference. At high concurrency, block-diffusion speculative decoding suffers from verification padding, rejected candidat…
cs.DC2026
BrownoutMoE: Structure-Aware Expert Grouping for Efficient and Accurate LLM Web-based Services
Yi Ding, Minxian Xu, Zhengxin Fang +2
Mixture-of-Experts (MoE) large language models (LLMs) are increasingly deployed in Web-facing services, where inference must be both accurate and responsive under bursty demand. Al…