Haotong Qin

Center for Project-Based Learning D-ITET, ETH Zürich
Office: ETZ D 97.4, Gloriastrasse 35, 8092 Zürich, Switzerland
Email: qinhaotong@gmail.com

I am a Postdoctoral Researcher at the Center for Project-Based Learning (PBL) D-ITET, ETH Zürich, Switzerland, working with PD Dr. Michele Magno. Previously, I received my Ph.D. degree from the State Key Laboratory of Complex & Critical Software Environment (SKLCCSE), Beihang University, supervised by Prof. Wei Li and Prof. Xianglong Liu. I obtained my B.E. degree from the School of Computer Science and Engineering (SCSE), Beihang University. I interned at Microsoft Research Asia, ByteDance AI Lab, and Tencent WeChat.

My research interest broadly includes efficient deep learning. Specifically, I focus on deep model compression (e.g., network binarization, quantization, and distillation), efficient generative model (e.g., efficient large language models and diffusion models), neuromorphic computing (e.g., spiking neural network), hardware acceleration (e.g., hardware-aware architecture search), etc. I am/was an Area Chair for BMCV'2024 and AISTATS'2025, a Program Committee member for ICML'(2023-2024), NeurIPS'(2023-2024), ICLR'(2024-2025), CVPR'(2023-2024), ICCV'2023, ECCV'2024, etc., and an Organizer or Challenge Chair for workshops at CVPR'(2022-2024), AAAI'(2022-2023), and IEEE CAI'2024.

For prospective collaborators, if you are interested in joining/visiting our lab or remotely working with us, please email me with your self-introduction, the project of interest, and CV to haotong.qin@pbl.ee.ethz.ch.

[Special Issue] Model Compression in the Era of Large Language Models @ Neural Networks

News

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 Excellent Graduate of Beijing 2024.
2024-01	I obtain the Baidu Scholarship 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 Scholarship 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).
2021-05	I obtain Huawei Scholarship 2021.
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

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

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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

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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

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

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

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

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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

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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

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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

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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

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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

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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

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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

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