Haoli Bai (柏昊立)

About

I am currently a researcher at the Language Model Lab, Huawei Hong Kong Research Center. I obtained my Ph.D. degree from The Chinese University of Hong Kong supervised by Prof. Michael R. Lyu and Prof. Irwin King, and the B.Eng. Degree from Yingcai Honors College of University of Electronic Science and Technology.

Our team's effort is on large language models with topics spanning from pre-training, post-training, to agentic AI (e.g., deep research and coding agent). I am also an experienced researcher in LLM efficiency, e.g., compression and acceleration of LLMs.

🔥 [Hiring] We are constantly looking for full-time researchers and research interns with solid algorithm or system background (Base: HK or Shenzhen). Please connect by E-Mail.

News

2026-1 🔥 We present SWE-Lego , the state-of-the-art supervised fine-tuning method for software issue resolving. All code, data, models are now opensourced. Project website.
2025-11 We will present the tutorial "Efficient Inference for Large Language Models – Algorithm, Model, and System" at EMNLP 2025. Tutorial website.
2025-11 I will give a talk on "Quantization and Pruning of Large Language Models: Challenges, Techniques and Opportunities" at LMG 2025.
2025-9 Our paper "A Simple Linear Patch Revives Layer-Pruned Large Language Models" is accepted by NeurIPS 2025.

Selected Publications

*: Equal contribution; #: Corresponding author; +: Project lead

SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving

Chaofan Tao^*, Jierun Chen^*, Yuxin Jiang^*, Kaiqi Kou^*, Shaowei Wang^*, Ruoyu Wang^*, Xiaohui Li^#, Sidi Yang, Yiming Du, Jianbo Dai, Zhiming Mao, Xinyu Wang, Lifeng Shang, Haoli Bai^#

arXiv Preprint 2601.01426.

Homepage Code Data & Models

A Simple Linear Patch Revives Layer-Pruned Large Language Models

Xinrui Chen, Haoli Bai^#+, Tao Yuan, Ruikang Liu, Kang Zhao, Xianzhi Yu, Lu Hou, Tian Guan, Yonghong He, Chun Yuan^#

Proceedings of the 39th conference on Neural Information Processing Systems (NeurIPS), 2025.

Code

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models

Ruikang Liu^*, Yuxuan Sun^*, Manyi Zhang^*, Haoli Bai^#+, Xianzhi Yu, Tiezheng Yu, Chun Yuan, Lu Hou^#

Conference on Language Modeling (COLM), 2025.

Code

FlatQuant: Flatness Matters for LLM Quantization

Yuxuan Sun^*, Ruikang Liu^*, Haoli Bai^#+, Han Bao, Kang Zhao, Yuening Li, Jiaxin Hu, Xianzhi Yu, Lu Hou, Chun Yuan, Xin Jiang, Wulong Liu, Jun Yao

International Conference on Machine Learning (ICML), 2025.

Code

Visually Guided Generative Text-Layout Pre-training for Document Intelligence

Zhiming Mao, Haoli Bai^#+, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Kam-Fai Wong

The North American Chapter of the Association for Computational Linguistics (NAACL), 2024.

Code

IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact

Ruikang Liu, Haoli Bai⁺, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, Chun Yuan

Findings of Annual Meeting of the Association for Computational Linguistics (ACL), 2024.

Code

Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models

Yingtao Zhang, Haoli Bai⁺, Haokun Lin, Jialin Zhao, Lu Hou, Carlo Vittorio Cannistraci

The Twelfth International Conference on Learning Representations (ICLR), 2024.

Code

Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding

Haoli Bai^*, Zhiguang Liu^*, Xiaojun Meng^*, Wentao Li, Shuang Liu, Nian Xie, Rongfu Zheng, Liangwei Wang, Lu Hou, Jiansheng Wei, Xin Jiang, Qun Liu

The 61th Annual Meeting of the Association for Computational Linguistics (ACL), 2023.

Towards Efficient Post-training Quantization of Pre-trained Language Models

Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael Lyu

Proceedings of the 36th conference on Neural Information Processing Systems (NeurIPS), 2022.

BinaryBERT: Pushing the Limit of BERT Quantization

Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jing Jin, Xin Jiang, Qun Liu, Michael Lyu, Irwin King

The 59th Annual Meeting of the Association for Computational Linguistics (ACL), 2021. Accepted with scores 5, 5, 4.

Code

Revisiting Parameter Sharing for Automatic Neural Channel Number Search

Haoli Bai^*, Jiaxing Wang^*, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael Lyu, Jian Cheng

Proceedings of the 34th conference on Neural Information Processing Systems (NeurIPS), 2020.

Code

Few Shot Network Compression via Cross Distillation

Haoli Bai, Jiaxiang Wu, Irwin King, Michael Lyu

Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020.

Code Poster

Neural Relational Topic Models for Scientific Article Analysis

Haoli Bai, Zhuangbin Chen, Michael Lyu, Irwin King, Zenglin Xu

Proceedings of The 27th International Conference on Information and Knowledge Management (CIKM), 2018.

Code

Invited Talks

"Quantization and Pruning of Large Language Models: Challenges, Techniques and Opportunities" at SLAI, 2025. [Slide]
"Efficient Inference for Large Language Models – Algorithm, Model, and System" at EMNLP Tutorial, 2025. [Tutorial website]
"Quantization and Pruning of Large Language Models: Challenges, Techniques and Opportunities" at LMG, 2025.

Projects

PocketFlow: An Automated Framework for Compressing and Accelerating DNNs

Code Doc

PocketFlow automatically searches for optimal model compression strategies such as network pruning, quantization, knowledge distillation with little human efforts, and also supports TFLite deployment on Android devices. It has collected 2600+ stars and 480+ forks.

Services

Area Chair

NeurIPS 2025

Senior PC Member

IJCAI 2021

PC Member

ICLR 22-25, ICML 21-25, NeurIPS 20-24, ACL ARR 25, COLM 25, ICCV 25, AAAI 19-21, IJCAI 20

Journal Reviewer

T-PAMI, Neural Networks, etc.

Selected Awards

Excellent Intern, Huawei Noah's Ark Lab 2021

AAAI Student Travel Grant 2020

ACM Student Travel Grant, CIKM 2018

CUHK Postgraduate Student Scholarship 2017-2021

Best Student Paper Runner-up, ACML 2016

National Scholarship 2015

Tang Lixin Scholarship 2015

Experience

Work Experience

Applied Scientist Intern at Amazon Devices 2021 Summer

Research Intern at Huawei Noah's Ark Lab 2020 Summer

Research Intern at Tencent AI Lab 2018 Summer

Teaching Assistant

CSCI3100: Software Engineering 2020 Spring

CSCI3100: Software Engineering 2019 Spring

CSCI1540: Introduction to C++ 2018 Fall

CSCI3100: Software Engineering 2018 Spring