Zeng

Yuchen Zeng (曾语晨)
PhD Candidate
University of Wisconsin-Madison
yzeng58 @ wisc . edu

   

About Me

I am a graduate student pursuing a PhD's degree in the Department of Computer Science at the University of Wisconsin-Madison. I am advised by Prof. Kangwook Lee. My current research interests include large language models and machine learning fairness. I received my Master's degree in Statistics from UW-Madison in 2020, where I was advised by Prof. Miaoyan Wang. Before joining UW-Madison, I completed my Bachelor's degree in Statistics from the School of Mathematical Sciences at Nankai University in 2019.

Publications

Large Language Models

Parameter-Efficient Fine-Tuning of State Space Models
Kevin Galim*, Wonjun Kang*, Yuchen Zeng*, Hyung Il Koo, Kangwook Lee

Can MLLMs Perform Text-to-Image In-Context Learning?
Yuchen Zeng*, Wonjun Kang*, Yicong Chen, Hyung Il Koo, Kangwook Lee
[Paper] [Code] [Summary] [45-Minute Talk]

The Expressive Power of Low-Rank Adaptation
Yuchen Zeng, Kangwook Lee
2024 International Conference on Learning Representation (ICLR)
[Paper] [Code] [Summary] [45-Minute Talk in Chinese]

Coded Prompts for Large Language Models
Ziqian Lin, Bryce Chen, Yuchen Zeng, Kangwook Lee
Neural Information Processing Systems 2023 (NeurIPS) R0-FoMo Workshop
[Paper] [Code]

LIFT: Language-Interfaced FineTuning for Non-Language Machine Learning Tasks
Tuan Dinh*, Yuchen Zeng*, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee
Neural Information Processing Systems 2022 (NeurIPS)
[Paper] [Code] [Summary] [5-Minute Video] [45-Minute Talk in Chinese]

Machine Learning Fairness

Federated Learning with Local Fairness Constraints
Yuchen Zeng, Hongxu Chen, Kangwook Lee
2023 IEEE International Symposium on Information Theory (ISIT)
[Paper]

Equal Improvability: A New Fairness Notion Considering the Long-Term Impact
Ozgur Guldogan*, Yuchen Zeng*, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee
2023 International Conference on Learning Representation (ICLR)
[Paper] [Code] [Summary] [5-Minute Video] [Article]

Outlier-Robust Group Inference via Gradient Space Clustering
Yuchen Zeng, Kristjan Greenewald, Kangwook Lee, Justin Solomon, Mikhail Yurochkin
Neural Information Processing Systems 2023 (NeurIPS) Distribution Shifts Workshop
[Paper] [Code]

Improving fairness via federated learning
Yuchen Zeng, Hongxu Chen, Kangwook Lee
Association for the Adavancement of Artificial Intelligence 2022 (AAAI) FL-AAAI Workshop
Machine Learning and Systems 2022 (MLSys) Cross-FL Workshop
[Paper] [Code] [Summary]

Tensor Learning

Multiway clustering via tensor block models
Miaoyan Wang, Yuchen Zeng
Neural Information Processing Systems 2019 (NeurIPS)
[Paper] [Code] [3-Minute Video]

Services and leadership

Selected to participant in Future Leaders Summit
Organizer of MLOPT Idea Seminar
Conference reviewer: NeurIPS, ICML, ICLR, TMLR

Work experience

Meta, Fall 2024
Mentored by Dr. Yipin Zhou

Microsoft, Summer 2024
Mentored by Dr. Andreas Christian Müller

MIT-IBM Watson AI Lab, Summer 2022
Mentored by Dr. Mikhail Yurochkin and Prof. Justin Solomon