Hao Zhang

According to our database, Hao Zhang authored at least 24 papers between 2021 and 2024.

Collaborative distances:

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

2024

Efficient LLM Scheduling by Learning to Rank.

Yichao Fu, Siqi Zhu, Runlong Su, Aurick Qiao, Ion Stoica, Hao Zhang

CoRR, 2024

MPC-Minimized Secure LLM Inference.

Deevashwer Rathee, Dacheng Li, Ion Stoica, Hao Zhang, Raluca A. Popa

CoRR, 2024

Empowering 1000 tokens/second on-device LLM prefilling with mllm-NPU.

Daliang Xu, Hao Zhang, Liming Yang, Ruiqi Liu, Gang Huang, Mengwei Xu, Xuanzhe Liu

CoRR, 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

Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length.

Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou

CoRR, 2024

Toward Inference-optimal Mixture-of-Expert Large Language Models.

Longfei Yun, Yonghao Zhuang, Yao Fu, Eric P. Xing, Hao Zhang

CoRR, 2024

MuxServe: Flexible Multiplexing for Efficient Multiple LLM Serving.

Jiangfei Duan, Runyu Lu, Haojie Duanmu, Xiuhong Li, Xingcheng Zhang, Dahua Lin, Ion Stoica, Hao Zhang

CoRR, 2024

DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving.

Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, Hao Zhang

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

Online Speculative Decoding.

Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Break the Sequential Dependency of LLM Inference Using Lookahead Decoding.

Yichao Fu, Peter Bailis, Ion Stoica, Hao Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving.

Jiangfei Duan, Runyu Lu, Haojie Duanmu, Xiuhong Li, Xingcheng Zhang, Dahua Lin, Ion Stoica, Hao Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica

Proceedings of the Forty-first International Conference on Machine Learning, 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

AdaMoE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models.

Zihao Zeng, Yibo Miao, Hongcheng Gao, Hao Zhang, Zhijie Deng

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

WiP: Efficient LLM Prefilling with Mobile NPU.

Daliang Xu, Hao Zhang, Liming Yang, Ruiqi Liu, Mengwei Xu, Xuanzhe Liu

Proceedings of the Workshop on Edge and Mobile Foundation Models, 2024

2023

LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers.

Dacheng Li, Rulin Shao, Anze Xie, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, Hao 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

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

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