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cs.DC2025
Fast LLM Post-training via Decoupled and Fastest-of-N Speculation
Rongxin Cheng, Kai Zhou, Xingda Wei +8
Rollout dominates the training time in large language model (LLM) post-training, where the trained model is used to generate tokens given a batch of prompts. This work, SpecActor,…
cs.CL2025★ 1 cited
SparseDoctor: Towards Efficient Chat Doctor with Mixture of Experts Enhanced Large Language Models
Jianbin Zhang, Yulin Zhu, Wai Lun Lo +3
Large language models (LLMs) have achieved great success in medical question answering and clinical decision-making, promoting the efficiency and popularization of the personalized…
cs.SI2025
Crowdsourced Homophily Ties Based Graph Annotation Via Large Language Model
Yu Bu, Yulin Zhu, Kai Zhou
Accurate graph annotation typically requires substantial labeled data, which is often challenging and resource-intensive to obtain. In this paper, we present Crowdsourced Homophily…