Dacheng Li
I am a second-year CS PhD at EECS, UC Berkeley, fortunately advised by Prof. Ion Stoica and Prof. Joseph Gonzalez in lmsys, Sky and BAIR.
I obtained my master in Machine Learning at CMU with Prof. Eric Xing and Prof. Hao Zhang . I obtained my undergraduate with double majors in Computer Science and Mathematics at UC San Diego with Prof. Zhuowen Tu . I also work closely with Prof. Song Han (MIT).
I study Machine Learning, in the context of modeling performance, scaling, system efficiency, framework usability, and theoratical support. My goal is to develop, support performant models at scale, and provide easily usable framework for people, to faciliate intelligence deployment in the real world. I am currently working on algorithms and systems around LLMs and diffusion models.
Also check out my girlfriend's webpage . She is a great CS PhD at UW.
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News
- 2024-08 Released LongVila, a seris of long-context VLM for videos.
- 2024-08 Released Marill, an efficient MPC framework for LLMs, extending the idea in MPCFormer.
- 2024-07 DistFlashAttn is accepted to COLM'2024.
- 2024-06 Joined Nvidia as a research intern, working on multi-modal foundation models with Prof. Han.
- 2024-05 Chatbot Arena is accepted to ICML'2024.
- 2024-03 VTC is accepted to OSDI'2024.
- 2024-02 S-lora and MCBench are accepted to MLsys'2024.
- 2023-09 The official paper of Vicuna (LLM-as-a-judge) is accepted to Neurips'2024.
- 2023-08 Joined Google as a student researcher, working on LLMs evaluation.
- 2023-06 Released a series of long-context models and evaluation toolkits LongChat.
- 2023-04 Released a compact open-sourced chatbot FastChat-T5.
- 2023-01 MPCFormer is accepted at ICLR'2023 as spotlight.
- 2022-12 A secure LLMs serving proposal is accepted at Amazon Research Awards.
- 2022-10 AMP is accepeted at Neurips'2022.
- 2021-03 DC-VAE is accepted at CVPR'2021.
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Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios N. Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica
ICML'24
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Fairness in Serving Large Language Models
Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica
OSDI'24
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S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Ying Sheng*, Shiyi Cao*, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica
MLsys'24
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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
Under submission to ICLR'24
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How long can opensource llms truly promise on context length
Dacheng Li*, Rulin Shao*, Anze Xie, Ying Sheng, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, and Hao Zhang
NeurIPS 2023 Instruction following workshop
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AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness
Dacheng Li , Hongyi Wang, Eric P. Xing, Hao Zhang
36th Conference on Neural Information Processing Systems (NeurIPS 2022)
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Dual Contradistinctive Generative AutoEncoder
Gaurav Parmar*, Dacheng Li* , Kwonjoon Lee*, Zhuowen Tu
2021 Conference on Computer Vision and Pattern Recognition (CVPR 2021)
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MPCFORMER: FAST, PERFORMANT AND PRIVATE TRANSFORMER INFERENCE WITH MPC
Dacheng Li* , Rulin Shao*, Hongyi Wang*, Han Guo, Eric P. Xing, Hao Zhang
ICLR'23 (Spotlight)
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Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
Zheng Lianmin*, 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
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 23)
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Does compressing activations help model parallel training?
Song Bian*, Dacheng Li* , Hongyi Wang, Eric P. Xing, Shivaram Venkataraman
MLSys'24
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