Approximating Martingale Process for Variance Reduction in Deep Reinforcement Learning with Large State Space. - Charlie Ruan (CoRR, 2022)

CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training. - A. Feder Cooper; Wentao Guo; Khiem Pham; Tiancheng Yuan; Charlie Ruan; Yucheng Lu; Christopher De Sa (NeurIPS, 2023)

Scale up with Order: Finding Good Data Permutations for Distributed Training. - Wentao Guo; Khiem Pham; Yucheng Lu; Tiancheng Yuan; Charlie F. Ruan; Christopher De Sa (CoRR, 2023)

Emerging Platforms Meet Emerging LLMs: A Year-Long Journey of Top-Down Development. - Siyuan Feng; Jiawei Liu 004; Ruihang Lai; Charlie F. Ruan; Yong Yu 001; Lingming Zhang 001; Tianqi Chen 001 (CoRR, 2024)

Local deployment of large-scale music AI models on commodity hardware. - Xun Zhou; Charlie Ruan; Zihe Zhao; Tianqi Chen 001; Chris Donahue (CoRR, 2024)

XGrammar: Flexible and Efficient Structured Generation Engine for Large Language Models. - Yixin Dong; Charlie F. Ruan; Yaxing Cai; Ruihang Lai; Ziyi Xu; Yilong Zhao; Tianqi Chen 001 (CoRR, 2024)

A System for Microserving of LLMs. - Hongyi Jin; Ruihang Lai; Charlie F. Ruan; Yingcheng Wang; Todd C. Mowry; Xupeng Miao; Zhihao Jia; Tianqi Chen 001 (CoRR, 2024)

WebLLM: A High-Performance In-Browser LLM Inference Engine. - Charlie F. Ruan; Yucheng Qin; Xun Zhou; Ruihang Lai; Hongyi Jin; Yixin Dong; Bohan Hou; Meng-Shiun Yu; Yiyan Zhai; Sudeep Agarwal; Hangrui Cao; Siyuan Feng; et al. (CoRR, 2024)

Productively Deploying Emerging Models on Emerging Platforms: A Top-Down Approach for Testing and Debugging. - Siyuan Feng; Jiawei Liu 004; Ruihang Lai; Charlie Ruan; Yong Yu 001; Lingming Zhang 001; Tianqi Chen 001 (Proc. ACM Softw. Eng., 2025)