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.
I will be graduating with my Ph.D. in Summer 2025 and am actively seeking full-time postdoctoral and industry researcher positions.
Publications
Deep Learning with Foundation Models
LLM Vulnerabilities in Targeted Email Collection
Yasmine Reis, Yuchen Zeng, Kangwook Lee
Under Review
TabFlex: Scaling Tabular Learning to Millions with Linear Attention
Yuchen Zeng, Wonjun Kang, Andreas Mueller
Neural Information Processing Systems 2024 (NeurIPS) TRL Workshop
[Paper]
Parameter-Efficient Fine-Tuning of State Space Models
Kevin Galim*, Wonjun Kang*, Yuchen Zeng*, Hyung Il Koo, Kangwook Lee
Neural Information Processing Systems 2024 (NeurIPS) FITML Workshop
[Paper]
Can MLLMs Perform Text-to-Image In-Context Learning?
Yuchen Zeng*, Wonjun Kang*, Yicong Chen, Hyung Il Koo, Kangwook Lee
2024 Conference on Language Modeling (COLM)
[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
Preprint
[Paper] [Code]
Improving fairness via federated learning
Yuchen Zeng, Hongxu Chen, Kangwook Lee
Preprint
[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
Recipient of 2024 COLM DEI Travel Scholarship
Selected to participate in Future Leaders Summit
Organizer of MLOPT Idea Seminar
Conference reviewer: NeurIPS, ICML, ICLR, TMLR, AISTATS
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