Zhuohan Li

According to our database, Zhuohan Li authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Optimizing Speculative Decoding for Serving Large Language Models Using Goodput.

Xiaoxuan Liu, Cade Daniel, Langxiang Hu, Woosuk Kwon, Zhuohan Li, Xiangxi Mo, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang

CoRR, 2024

Fairness in Serving Large Language Models.

Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica

Proceedings of the 18th USENIX Symposium on Operating Systems Design and Implementation, 2024

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

What is the State of Memory Saving for Model Training?

Xiaoxuan Liu, Siddharth Jha, Chuyan Zhu, Zhuohan Li, Alvin Cheung

CoRR, 2023

High-throughput Generative Inference of Large Language Models with a Single GPU.

Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang

CoRR, 2023

Efficient Memory Management for Large Language Model Serving with PagedAttention.

Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, Ion Stoica

Proceedings of the 29th Symposium on Operating Systems Principles, 2023

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving.

Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Optimizing the Communication of Model Parallelism.

Yonghao Zhuang, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph Gonzalez, Ion Stoica, Hao Zhang, Hexu Zhao

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU.

Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang

Proceedings of the International Conference on Machine Learning, 2023

2022

Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning.

Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica

CoRR, 2022

Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning.

Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica

Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation, 2022

2021

Rearchitecting In-Memory Object Stores for Low Latency.

Danyang Zhuo, Kaiyuan Zhang, Zhuohan Li, Siyuan Zhuang, Stephanie Wang, Ang Chen, Ion Stoica

Proc. VLDB Endow., 2021

Hoplite: efficient and fault-tolerant collective communication for task-based distributed systems.

Siyuan Zhuang, Zhuohan Li, Danyang Zhuo, Stephanie Wang, Eric Liang, Robert Nishihara, Philipp Moritz, Ion Stoica

Proceedings of the ACM SIGCOMM 2021 Conference, Virtual Event, USA, August 23-27, 2021., 2021

Simple and Automatic Distributed Machine Learning on Ray.

Hao Zhang, Zhuohan Li, Lianmin Zheng, Ion Stoica

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models.

Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers.

Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez

CoRR, 2020

Hoplite: Efficient Collective Communication for Task-Based Distributed Systems.

Siyuan Zhuang, Zhuohan Li, Danyang Zhuo, Stephanie Wang, Eric Liang, Robert Nishihara, Philipp Moritz, Ion Stoica

CoRR, 2020

Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers.

Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View.

Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun, Bin Dong, Tao Qin, Liwei Wang, Tie-Yan Liu

CoRR, 2019

Fast Structured Decoding for Sequence Models.

Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, Zhi-Hong Deng

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Training of BERT by Progressively Stacking.

Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu

Proceedings of the 36th International Conference on Machine Learning, 2019

Hint-Based Training for Non-Autoregressive Machine Translation.

Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao Qin, Liwei Wang, Tie-Yan Liu

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Towards Binary-Valued Gates for Robust LSTM Training.

Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Liwei Wang, Tie-Yan Liu

Proceedings of the 35th International Conference on Machine Learning, 2018