Towards Binary-Valued Gates for Robust LSTM Training. - Zhuohan Li 001; Di He 001; Fei Tian; Wei Chen 034; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (ICML, 2018)

Hint-Based Training for Non-Autoregressive Machine Translation. - Zhuohan Li 001; Zi Lin; Di He 001; Fei Tian; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (EMNLP/IJCNLP (1), 2019)

Efficient Training of BERT by Progressively Stacking. - Linyuan Gong; Di He 001; Zhuohan Li 001; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (ICML, 2019)

Fast Structured Decoding for Sequence Models. - Zhiqing Sun; Zhuohan Li 001; Haoqing Wang; Di He 001; Zi Lin; Zhi-Hong Deng 001 (NeurIPS, 2019)

Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View. - Yiping Lu 001; Zhuohan Li 001; Di He 001; Zhiqing Sun; Bin Dong 001; Tao Qin 001; Liwei Wang 001; Tie-Yan Liu (CoRR, 2019)

Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. - Zhuohan Li 001; Eric Wallace; Sheng Shen 001; Kevin Lin; Kurt Keutzer; Dan Klein 001; Joey Gonzalez (ICML, 2020)

Hoplite: Efficient Collective Communication for Task-Based Distributed Systems. - Siyuan Zhuang; Zhuohan Li 001; Danyang Zhuo; Stephanie Wang; Eric Liang; Robert Nishihara; Philipp Moritz; Ion Stoica (CoRR, 2020)

Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers. - Zhuohan Li 001; Eric Wallace; Sheng Shen 001; Kevin Lin; Kurt Keutzer; Dan Klein 001; Joseph E. Gonzalez (CoRR, 2020)

TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models. - Zhuohan Li 001; Siyuan Zhuang; Shiyuan Guo; Danyang Zhuo; Hao Zhang 025; Dawn Song; Ion Stoica (ICML, 2021)

Simple and Automatic Distributed Machine Learning on Ray. - Hao Zhang 025; Zhuohan Li 001; Lianmin Zheng; Ion Stoica (KDD, 2021)

Hoplite: efficient and fault-tolerant collective communication for task-based distributed systems. - Siyuan Zhuang; Zhuohan Li 001; Danyang Zhuo; Stephanie Wang; Eric Liang; Robert Nishihara; Philipp Moritz; Ion Stoica (SIGCOMM, 2021)

Rearchitecting In-Memory Object Stores for Low Latency. - Danyang Zhuo; Kaiyuan Zhang 001; Zhuohan Li 001; Siyuan Zhuang; Stephanie Wang; Ang Chen 001; Ion Stoica (Proc. VLDB Endow., 2021)

Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. - Lianmin Zheng; Zhuohan Li 001; Hao Zhang 025; Yonghao Zhuang 001; Zhifeng Chen; Yanping Huang; Yida Wang 003; Yuanzhong Xu; Danyang Zhuo; Eric P. Xing; Joseph E. Gonzalez; Ion Stoica (OSDI, 2022)

Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. - Lianmin Zheng; Zhuohan Li 001; Hao Zhang 025; Yonghao Zhuang 001; Zhifeng Chen; Yanping Huang; Yida Wang 003; Yuanzhong Xu; Danyang Zhuo; Joseph E. Gonzalez; Ion Stoica (CoRR, 2022)

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Beidi Chen; Percy Liang; Christopher Ré; Ion Stoica; Ce Zhang 001 (ICML, 2023)

On Optimizing the Communication of Model Parallelism. - Yonghao Zhuang 001; Lianmin Zheng; Zhuohan Li 001; Eric P. Xing; Qirong Ho; Joseph Gonzalez 001; Ion Stoica; Hao Zhang 025; Hexu Zhao (MLSys, 2023)

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. - Lianmin Zheng; Wei-Lin Chiang; Ying Sheng 007; Siyuan Zhuang; Zhanghao Wu; Yonghao Zhuang 001; Zi Lin; Zhuohan Li 001; Dacheng Li; Eric P. Xing; Hao Zhang 025; Joseph E. Gonzalez; et al. (NeurIPS, 2023)

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving. - Zhuohan Li 001; Lianmin Zheng; Yinmin Zhong; Vincent Liu 001; Ying Sheng 007; Xin Jin 008; Yanping Huang; Zhifeng Chen; Hao Zhang 025; Joseph E. Gonzalez; Ion Stoica (OSDI, 2023)

Efficient Memory Management for Large Language Model Serving with PagedAttention. - Woosuk Kwon; Zhuohan Li 001; Siyuan Zhuang; Ying Sheng 007; Lianmin Zheng; Cody Hao Yu; Joseph Gonzalez 001; Hao Zhang 025; Ion Stoica (SOSP, 2023)

High-throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Daniel Y. Fu; Zhiqiang Xie; Beidi Chen; Clark W. Barrett; Joseph E. Gonzalez; Percy Liang; Christopher Ré; et al. (CoRR, 2023)

What is the State of Memory Saving for Model Training? - Xiaoxuan Liu; Siddharth Jha; Chuyan Zhu; Zhuohan Li 001; Alvin Cheung (CoRR, 2023)

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. - Lianmin Zheng; Wei-Lin Chiang; Ying Sheng 007; Tianle Li; Siyuan Zhuang; Zhanghao Wu; Yonghao Zhuang 001; Zhuohan Li 001; Zi Lin; Eric P. Xing; Joseph E. Gonzalez; Ion Stoica; et al. (ICLR, 2024)

Fairness in Serving Large Language Models. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Banghua Zhu; Zhuohan Li 001; Danyang Zhuo; Joseph E. Gonzalez; Ion Stoica (OSDI, 2024)

Optimizing Speculative Decoding for Serving Large Language Models Using Goodput. - Xiaoxuan Liu; Cade Daniel; Langxiang Hu; Woosuk Kwon; Zhuohan Li 001; Xiangxi Mo; Alvin Cheung; Zhijie Deng; Ion Stoica; Hao Zhang 025 (CoRR, 2024)

Empowering Large Language Models with Efficient and Automated Systems - Zhuohan Li 001 (2024)

Jenga: Effective Memory Management for Serving LLM with Heterogeneity. - Chen Zhang 001; Kuntai Du; Shu Liu; Woosuk Kwon; Xiangxi Mo; Yufeng Wang; Xiaoxuan Liu; Kaichao You; Zhuohan Li 001; Mingsheng Long; Jidong Zhai; Joseph Gonzalez 001; et al. (CoRR, 2025)