Haotong Qin

Center for Project-Based Learning D-ITET, ETH Zürich
Office: ETZ, Gloriastrasse 35, 8092 Zürich, Switzerland
Email: haotong.qin@pbl.ee.ethz.ch

I am a Postdoctoral Researcher at Center for Project-Based Learning D-ITET, ETH Zürich, working with PD Dr. Michele Magno. Previously, I obtained my Ph.D. degree from the State Key Laboratory of Complex & Critical Software Environment, Beihang University, supervised by Prof. Wei Li and Prof. Xianglong Liu. I was a Visiting Scholar at Computer Vision Laboratory, ETH Zürich. I obtained my B.E. degree from the School of Computer Science and Engineering, Beihang University. I was a Research Scientist Intern at Microsoft Research, Tencent, and ByteDance.

My research interests lie in Discrete AI, that is, achieving Efficient AI/ML Systems via Extreme Discretization, including compression algorithms (e.g., binarization, quantization), efficient foundation models (e.g., large language models and diffusion models), and their deployment in edge systems (e.g., robotics, embedded hardware). I was awarded by ByteDance PhD Fellowship, Baidu PhD Fellowship, Zeiss Abbe Fellowship, DAAD AInet Fellowship, MLCommons/Meta ML and Systems Rising Stars, WAIC "YunFan" Rising Stars, KAUST Rising Stars in AI, Electronics Best PhD Thesis Award, CSIG Best PhD Thesis Award, and the Best Paper Award at IJCAI-GLOW 2025. I'm selected as Stanford's Top 2% Scientists Worldwide (2025). I am/was an Area Chair for CVPR, NeurIPS, ACM MM, AISTATS, BMVC, etc., a Program Committee member for ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, IROS, etc.

[Workshop] Binary and Extreme Quantization for Computer Vision @ ICCV 2025
[Workshop] Toward Robust Compressed Foundation Models in the Real World @ IJCAI 2025
[Special Issue] Cognitive Robustness of Foundation Models @ Pattern Analysis and Applications

News

2025-11 Three papers are accepted by AAAI 2026.
2025-09 I'm selected into Stanford University's list of the World's Top 2% Scientists.
2025-09 Two papers are accepted by NeurIPS 2025.
2025-09 I am serving as an Area Chair for CVPR 2026.
2025-06 One oral papers is accepted by IROS 2025.
2025-05 I am serving as an Area Chair for BMVC 2025.
2025-05 Three papers are accepted by ICML 2025.
2025-04 I am selected as one of the Young Researchers of the 12th Heidelberg Laureate Forum (HLF).
2025-04 One paper is accepted by RSS 2025.
2025-04 I am serving as an Area Chair for NeurIPS 2025.
2025-03 I am serving as an Area Chair for ACM MM 2025.
2025-03 I obtain the MLCommons ML and Systems Rising Stars 2025 (38 people worldwide).
2025-02 Two papers are accepted by CVPR 2025.
2025-01 Two papers are accepted by ICLR 2025.
2025-01 One oral papers are accepted by WWW 2025.
2024-12 Two oral papers are accepted by AAAI 2025.
2024-12 I am serving as an Area Chair for IJCNN 2025.
2024-11 I obtain the CSIG 2024 Outstanding PhD Thesis Award (10 people nationwide).
2024-10 I am serving as an Area Chair for AISTATS 2025.
2024-09 Four (one spotlight) papers and one workshop paper are accepted by NeurIPS 2024.
2024-06 I obtain the WAIC Yunfan Award (Rising Star) 2024 (15 people worldwide).
2024-05 I am serving as an Guest Editor for Neural Networks.
2024-05 One paper for LLM quantization is accepted by ACL 2024.
2024-05 Five papers (one oral) for efficient LLMs and DMs are accepted by ICML 2024.
2024-05 I am serving as an Area Chair for BMVC 2024.
2024-04 I obtain the Electronics 2023 Best PhD Thesis Award (2 people worldwide).
2024-01 I obtain the Outstanding Graduate of Beijing 2024.
2024-01 I obtain the Baidu PhD Fellowship 2023 (10 people worldwide).
2023-09 Two first-authored papers (one spotlight) are model quantization is accepted by NeurIPS 2023.
2023-09 I obtain China National Scholarship (3rd time).
2023-06 We release our open source project "Awesome Efficient AIGC".
2023-05 I am named one of the CVPR 2023 Outstanding Reviewers.
2023-04 One first-authored paper for data-free quantization is accepted by IEEE TPAMI.
2023-04 One first-authored paper for model binarization benchmark is accepted by ICML 2023.
2023-04 I obtain the DAAD AInet Fellowship 2023.
2023-02 One first-authored paper for FSMN binarization is accepted by IEEE TNNLS.
2022-12 I am selected for the Rising Stars in AI Symposium 2023 organized by KAUST AI initiative.
2022-10 I obtain the ByteDance PhD Fellowship 2022.
2022-10 Our BiPointNet (ICLR'21) integrated into Amazon's Deep Graph Library (DGL).
2022-09 One first-authored paper for model binarization is accepted by IJCV.
2022-06 One co-authored paper for ViT quantization is accepted by ACM MM 2022.
2022-06 I obtain the Beihang Top-10 PhD Students Award 2022.
2022-05 Our BiBERT (ICLR'22) integrated into Baidu's deep learning platform PaddlePaddle.
2022-04 One first-authored paper for FSMN binarization is accepted by IJCAI 2022.
2022-03 Our survey paper for binary neural networks is selected to ESI Highly Cited Papers
2022-01 One first-authored paper for BERT binarization is accepted by ICLR 2022.
2021-09 Our BiPointNet (ICLR'21) obtain the Most Popular Paper in Beijing Area.
2021-09 I obtain China National Scholarship 2021 (2nd time).
2021-03 One co-first-authored oral paper for data-free quantization is accepted by CVPR 2021.
2021-01 One first-authored paper for PointNet binarization is accepted by ICLR 2021.
2020-09 I obtain China National Scholarship 2020.
2020-09 We release our open source project "Awesome Model Quantization".
2020-02 One first-authored paper for model binarization is accepted by CVPR 2020.
2020-02 One first-authored survey paper for binary neural networks is accepted by PR.

Selected Publications

  1. AAAI
    First-Order Error Matters: Accurate Compensation for Quantized Large Language Models
    Xingyu Zheng†, Haotong Qin†, Yuye Li, Haoran Chu, Jiakai Wang, Jinyang Guo, Michele Magno, Xianglong Liu
    In AAAI Conference on Artificial Intelligence (AAAI), 2026
    PDF Code
  2. AAAI
    TR-DQ: Time-Rotation Diffusion Quantization
    Yihua Shao, Deyang Lin, Minxi Yan, Siyu Chen, Fanhu Zeng, Minwen Liao, Ao Ma, Ziyang Yan, Haozhe Wang, Yan Wang*, Zhi Chen, Xiaofeng Cao, Haotong Qin*, Hao Tang*, Jingcai Guo
    In AAAI Conference on Artificial Intelligence (AAAI), 2026
    PDF Code
  3. NeurIPS
    S2Q-VDiT: Accurate Quantized Video Diffusion Transformer with Salient Data and Sparse Token Distillation
    Weilun Feng†, Haotong Qin†, Chuanguang Yang, Xiangqi Li, Han Yang, Yuqi Li, Zhulin An, Libo Huang, Michele Magno, Yongjun Xu
    In Conference on Neural Information Processing Systems (NeurIPS), 2025
    PDF Code
  4. ICML
    SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
    Wei Huang, Haotong Qin*, Yangdong Liu, Yawei Li, Qinshuo Liu, Xianglong Liu, Luca Benini, Michele Magno, Shiming Zhang*, Xiaojuan Qi*
    In International Conference on Machine Learning (ICML), 2025
    PDF Code
  5. IROS
    FSDP: Fast and Safe Data-Driven Overtaking Trajectory Planning for Head-to-Head Autonomous Racing Competitions
    Cheng Hu, Jihao Huang, Wule Mao, Yonghao Fu, Xuemin Chi, Haotong Qin*, Nicolas Baumann, Zhitao Liu, Michele Magno, Lei Xie*
    In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS Oral), 2025
    PDF Code
  6. RSS
    Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models
    Nicolas Baumann, Cheng Hu, Paviththiren Sivasothilingam, Haotong Qin, Lei Xie, Michele Magno, Luca Benini
    In Robotics: Science and Systems (RSS), 2025
    PDF Code
  7. CVPR
    PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution
    Libo Zhu, Jianze Li, Haotong Qin*, Yulun Zhang*, Yong Guo, Xiaokang Yang
    In Computer Vision and Pattern Recognition (CVPR), 2025
    PDF Code
  8. AAAI
    MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
    Weilun Feng†, Haotong Qin†, Chuanguang Yang, Zhulin An, Libo Huang, Boyu Diao, Fei Wang, Renshuai Tao, Yongjun Xu, Michele Magno
    In AAAI Conference on Artificial Intelligence (AAAI Oral), 2025
    PDF Code
  9. AAAI
    ODDN: Addressing Unpaired Data Challenges in Open-World Deepfake Detection on Online Social Networks
    Renshuai Tao, Manyi Le, Chuangchuang Tan, Huan Liu, Haotong Qin*, Yao Zhao
    In AAAI Conference on Artificial Intelligence (AAAI Oral), 2025
    PDF
  10. NeurIPS
    Binarized Diffusion Model for Image Super-Resolution
    Zheng Chen, Haotong Qin*, Yong Guo, Xiongfei Su, Xin Yuan, Linghe Kong, Yulun Zhang*
    In Conference on Neural Information Processing Systems (NeurIPS), 2024
    PDF Code
  11. NeurIPS
    BiDM: Pushing the Limit of Quantization for Diffusion Models
    Xingyu Zheng, Xianglong Liu, Yichen Bian, Xudong Ma, Yulun Zhang, Jiakai Wang, Jinyang Guo, Haotong Qin
    In Conference on Neural Information Processing Systems (NeurIPS), 2024
    PDF Code
  12. ICML
    Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
    Haotong Qin†, Xudong Ma†, Xingyu Zheng, Xiaoyang Li, Yang Zhang, Shouda Liu, Jie Luo, Xianglong Liu, Michele Magno
    In International Conference on Machine Learning (ICML Oral), 2024
    PDF Code
  13. ICML
    BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
    Wei Huang, Yangdong Liu, Haotong Qin*, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi
    In International Conference on Machine Learning (ICML), 2024
    PDF Code IEEE Spectrum
  14. ICML
    Flexible Residual Binarization for Image Super-Resolution
    Yulun Zhang†, Haotong Qin†, Zixiang Zhao, Xianglong Liu, Martin Danelljan, Fisher Yu
    In International Conference on Machine Learning (ICML), 2024
    PDF
  15. NeurIPS
    QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution
    Haotong Qin†, Yulun Zhang†, Yifu Ding, Yifan Liu, Xianglong Liu, Martin Danelljan, Fisher Yu
    In Conference on Neural Information Processing Systems (NeurIPS Spotlight), 2023
    PDF Code
  16. NeurIPS
    BiMatting: Efficient Video Matting via Binarization
    Haotong Qin†, Lei Ke†, Xudong Ma, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Xianglong Liu, Fisher Yu
    In Conference on Neural Information Processing Systems (NeurIPS), 2023
    PDF Code
  17. ICML
    BiBench: Benchmarking and Analyzing Network Binarization
    Haotong Qin†, Mingyuan Zhang†, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu
    In International Conference on Machine Learning (ICML), 2023
    PDF Code
  18. ICLR
    BiBERT: Accurate Fully Binarized BERT
    Haotong Qin†, Yifu Ding†, Mingyuan Zhang†, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu
    In International Conference on Learning Representations (ICLR), 2022
    PDF Code
  19. IJCAI
    BiFSMN: Binary Neural Network for Keyword Spotting
    Haotong Qin†, Xudong Ma†, Yifu Ding†, Xiaoyang Li, Yang Zhang, Yao Tian, Zejun Ma, Jie Luo, Xianglong Liu
    In International Joint Conference on Artificial Intelligence (IJCAI), 2022
    PDF Code
  20. CVPR
    Diversifying Sample Generation for Accurate Data-Free Quantization
    Xiangguo Zhang†, Haotong Qin†, Yifu Ding, Ruihao Gong, Qinghua Yan, Renshuai Tao, Yuhang Li, Fengwei Yu, Xianglong Liu
    In Computer Vision and Pattern Recognition (CVPR Oral), 2021
    PDF Code
  21. ICLR
    BiPointNet: Binary Neural Network for Point Clouds
    Haotong Qin†, Zhongang Cai†, Mingyuan Zhang†, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu, Hao Su
    In International Conference on Learning Representations (ICLR), 2021
    PDF Code
  22. CVPR
    Forward and Backward Information Retention for Accurate Binary Neural Networks
    Haotong Qin, Ruihao Gong, Xianglong Liu, Mingzhu Shen, Ziran Wei, Fengwei Yu, Jingkuan Song
    In Computer Vision and Pattern Recognition (CVPR), 2020
    PDF Code
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