Yichen Wu / 吴一尘（Pronounced: Ee-chen Woo）

Yichen Wu / 吴一尘（Pronounced: Ee-chen Woo）

MGB/Harvard Medical School, Boston, MA 02155
Email: wuyichen.am97@gmail.com
[Google Scholar] [Github] [Linkedin]

Biography

I am currently a Postdoctoral Research Fellow at MGB/Harvard Medical School, working with Prof. Xiang Li and Prof. Quanzheng Li . Recently, I have focused on Continual Learning/Knowledge Editing, MLLM, Model Quantization and Medical Agents.

I received my Ph.D. in Computer Science from the City University of Hong Kong under the supervision of Prof. Ying Wei and Prof. Kede Ma. Before that, I received my M.Sc degree under the supervision of Prof. Deyu Meng from the School of Mathematics and Statistics, Xi'an Jiaotong University. Additionally, I hold dual B.S. degrees from Beijing Jiaotong University, where I majored in Mathematics and minored in Economics and Management. Also, I was a visiting scholar in the Visual Computing Group, Harvard, supervised by Prof. Hanspeter Pfister (IEEE Fellow, ACM Fellow) and working closely with Dr. Wanhua Li.

If you are interested in my research or would like to work with me, feel free to contact me.

Research Interest

My research interests include continual learning, transfer learning, and meta-learning. Currently, I am focusing on designing algorithms to enhance the efficiency of LLMs in handling continual learning and exploring methods to utilize transformers within LLMs efficiently. Additionally, I am dedicated to investigating the following research topics:

Forgetting/hallucination problems
Optimize algorithms to accelerate LLM
Continual Learning in Medical Applications
Weakly Supervised Learning (including noisy/imbalanced settings)

Research Experiences

Harvard VCG Lab, MA, U.S.

Visiting Scholar, Sep. 2024 ~ Now

Supervised by Prof. Hanspeter Pfister (IEEE Fellow, ACM Fellow) and working closely with Dr. Wanhua Li.

Youtu Lab (Original Jarvis Research Center)@Tencent, Shenzhen, China

Research Intern, Sep. 2023 ~ April. 2024

Supervised by Prof. Yefeng Zheng (IEEE Fellow, AIMBE Fellow) and Dr. Hong Wang

AI Lab (Machine Learning Center)@Tencent, Shenzhen, China

Research Intern (Tencent Rhino Bird Elite Talent Program), Feb. 2021 ~ Aug. 2023

Supervised by Dr. Long-Kai Huang and Dr. Peilin Zhao

News

[07/2025] One paper about knowledge editing has been accepted for COLM 2025! Congrats to Zhiyi and Binjie!
[06/2025] Two papers have been accepted for ICCV 2025! Congrats to Minghan and Yinan!
[04/2025] One paper is accepted for an Highlight at CVPR 2025! Congrats to Haowen!
[02/2025] Our SD-LoRA is accepted for an oral presentation at ICLR 2025!
[01/2025] Our paper “SD-LoRA: Scalable Low-Rank Adaptation for Class Incremental Learning” has been accepted by ICLR 2025!
[01/2025] Our paper “Adaptive Weighting based Metal Artifact Reduction in CT Images” has been accepted by TMI.
[12/2024] Attending NeurIPS 2024 in Vancouver—looking forward to connecting!
[09/2024] One paper has been accepted by IJCV.
[09/2024] Our Dual-quant about the LLM Quantization is accepted for an oral presentation at NeurIPS 2024!
[09/2024] Thrilled to have spent a year as a visiting scholar at Harvard!
[06/2024] Happy to receive the ICML Travel Award (2024)!
[05/2024] Honored to receive the ICLR 2024 Outstanding Honorable Mention Award !
[05/2024] Two papers related to continual learning are accepted by ICML 2024.
[04/2024] Happy to be selected as a DAAD AInet Fellow (2024)!
[01/2024] Our VR-MCL for Meta-Continual Learning is accepted in ICLR 2024 (oral, 1.2% of submissions)!
[01/2024] I have been invited to serve as a reviewer for CVPR2024.
[09/2023] I have been invited to serve as a reviewer for ICLR2024.
[06/2023] I have been invited to be a reviewer for TNNLS.
[07/2023] Our CBA for alleviating the recency bias in continual learning is accepted in ICCV 2023.
[01/2023] Our L2AC for imbalanced semi-supervised learning is accepted in ICLR 2023.
[10/2022] I am honored with the NeurIPS 2022 travel award!
[09/2022] Our ATU for task augmentation in meta-learning is accepted in NeurIPS 2022 (spotlight).
[09/2021] Begin my journey at the City University of Hong Kong under the supervision of Prof. Ying Wei.
[06/2021] I graduate from XJTU, with heartfelt thanks to my supervisor, Deyu Meng.
[05/2021] One paper is accepted in MICCAI 2021.
[03/2021] Our survey paper on single-image and video deraining is accepted in Science China Information Sciences.
[12/2020] Our MSLC for learning with noisy labels is accepted in AAAI 2021.
[12/2020] One paper is accepted in Knowledge-Based System.
[09/2018] Begin my journey in IID Lab, Xi'an Jiaotong University under the supervision of Prof. Deyu Meng.

Selected Publications [Full List] (^Co-first author; *Corresponding author)

	SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning. Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei International Conference on Learning Representation, (ICLR), 2025. (Oral) [Paper] [Code] [量子位(Qubit)]
	DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs. Haokun Lin^, Haobo Xu^, Yichen Wu^, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei Neural Information Processing Systems,(NeurIPS), 2024. (Oral) [Paper] [Code] [Website]
	Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization Yichen Wu^, Hong Wang^, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang International Conference on Machine Learning (ICML), 2024. [Paper] [Code]
	Federated Continual Learning via Prompt-based Dual Knowledge Transfer Hongming Piao^, Yichen Wu^, Dapeng Wu, Ying Wei* International Conference on Machine Learning (ICML), 2024. [Paper] [Code]
	Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction Yichen Wu, Long-kai Huang, Renzhen Wang, Deyu Meng, Ying Wei. International Conference on Learning Representation (ICLR), 2024. (Oral) (Outstanding Paper Award Honorable Mention, 0.23% acceptance rate) [Paper] [Code]
	Adversarial Task Up-sampling for Meta-learning Yichen Wu, Long-Kai Huang, Ying Wei Neural Information Processing Systems, (NeurIPS), 2022. (Spotlight) [Paper] [Code]
	Learning to Purify Noisy Labels via Meta Soft Label Corrector Yichen Wu, Jun Shu, Qi Xie, Qian Zhao, Deyu Meng* Association for the Advancement of Artificial Intelligence (AAAI), 2021. [Paper] [Code]
	CBA: Improving Online Continual Learning via Continual Bias Adaptor Quanziang Wang, Renzhen Wang, Yichen Wu, Xixi Jia, Qian Zhao, Deyu Meng International Conference on Computer Vision(ICCV), 2023. [Paper] [Code]
	Imbalanced Semi-supervised Learning with Bias Adaptive Classifier Renzhen Wang, Xixi Jia, Quanziang Wang, Yichen Wu, Deyu Meng* International Conference on Learning Representation(ICLR), 2023. [Paper] [Code]
	Survey on Rain Removal From Videos or A Single Image Hong Wang, Yichen Wu, Minghan Li, Qian Zhao, Deyu Meng* SCIENCE CHINA Information Sciences(SCIS), 2022. [Paper] [Code]
	Neighbor Matching for Semi-supervised Learning Renzhen Wang, Yichen Wu, Huai Chen, Lisheng Wang, Deyu Meng* Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [Paper] [Code]

Selected Honors

ICML Travel Award, 2024.
ICLR Outstanding Paper Award Honorable Mention, 2024.
DAAD AInet Fellowship, Germany, 2024.
Institutional Research Tuition Scholarship of CityU, 2023, 2024.
NeurIPS Scholar Award, 2022.
Tencent Rhino-Bird Elite, 2021.
Outstanding Master's Degree Graduates of XJTU, 2021.
National third prize in Graduate Student Mathematical Modeling Competition, 2019.
Scholarship of BJTU/XJTU, 2015, 2016, 2017, 2018, 2019, 2020.

Talks

Invited Presentation at AI Time.
Invited talk at the Deep Learning and Optimization Seminar .
Invited talk at WizTalk about the published ICML24 paper.

Services

Journal & Conference Reviewer:

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Science China Information Sciences (SCIS)
Neurocomputing
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Transactions on Machine Learning Research (TMLR)
Association for the Advancement of Artificial Intelligence (AAAI)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
International Conference on Computer Vision (ICCV)
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Neural Information Processing Systems (NeurIPS)
International Conference on Learning Representation (ICLR)
International Conference on Machine Learning (ICML)
Conference on Language Modeling (COLM)

	SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning. Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei International Conference on Learning Representation, (ICLR), 2025. (Oral) [Paper] [Code] [量子位(Qubit)]
	DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs. Haokun Lin^, Haobo Xu^, Yichen Wu^, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei Neural Information Processing Systems,(NeurIPS), 2024. (Oral) [Paper] [Code] [Website]
	Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization Yichen Wu^, Hong Wang^, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang International Conference on Machine Learning (ICML), 2024. [Paper] [Code]
	Federated Continual Learning via Prompt-based Dual Knowledge Transfer Hongming Piao^, Yichen Wu^, Dapeng Wu, Ying Wei* International Conference on Machine Learning (ICML), 2024. [Paper] [Code]
	Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction Yichen Wu, Long-kai Huang, Renzhen Wang, Deyu Meng, Ying Wei. International Conference on Learning Representation (ICLR), 2024. (Oral) (Outstanding Paper Award Honorable Mention, 0.23% acceptance rate) [Paper] [Code]
	Adversarial Task Up-sampling for Meta-learning Yichen Wu, Long-Kai Huang, Ying Wei Neural Information Processing Systems, (NeurIPS), 2022. (Spotlight) [Paper] [Code]
	Learning to Purify Noisy Labels via Meta Soft Label Corrector Yichen Wu, Jun Shu, Qi Xie, Qian Zhao, Deyu Meng* Association for the Advancement of Artificial Intelligence (AAAI), 2021. [Paper] [Code]
	CBA: Improving Online Continual Learning via Continual Bias Adaptor Quanziang Wang, Renzhen Wang, Yichen Wu, Xixi Jia, Qian Zhao, Deyu Meng International Conference on Computer Vision(ICCV), 2023. [Paper] [Code]
	Imbalanced Semi-supervised Learning with Bias Adaptive Classifier Renzhen Wang, Xixi Jia, Quanziang Wang, Yichen Wu, Deyu Meng* International Conference on Learning Representation(ICLR), 2023. [Paper] [Code]
	Survey on Rain Removal From Videos or A Single Image Hong Wang, Yichen Wu, Minghan Li, Qian Zhao, Deyu Meng* SCIENCE CHINA Information Sciences(SCIS), 2022. [Paper] [Code]
	Neighbor Matching for Semi-supervised Learning Renzhen Wang, Yichen Wu, Huai Chen, Lisheng Wang, Deyu Meng* Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [Paper] [Code]