Zhuoyan Xu Ph.D. candidate Department of Statistics, Computer Science University of Wisconsin-Madison, US Contact: zhuoyan.xu [at] wisc [dot] edu Office 5388, Department of Computer Sciences, UW-Madison Google Scholar | Github | LinkedIn | CV

About Me

I am a Ph.D. candidate in Statistics at the University of Wisconsin-Madison co-advised by Prof. Yingyu Liang , Prof. Yin Li and Prof. Yiqiao Zhong . I am also fortunate to work with Prof. Kris Sankaran . I obtained my M.S. degree in Computer Science from UW-Madison. Prior to that, I obtained my B.S. degree in Statistics from Wuhan University in 2019.

I was an Applied Scientist Intern in summer 2024 at Amazon AWS AI, Bellevue. I was a Machine Learning Engineer intern in John Deere Intelligent Solutions Group in summer 2022. I also had an internship at China Merchants Bank, Shanghai.

My research interest includes Foundation Model (including large vision, language and multimodal models) and Representation Learning. I am interested in investigating and analyzing behavior of foundation models, aiming to enhance their adaptation to downstream tasks with improved accuracy and greater efficiency.

News

• [12/17/2024]: Passed my prelim exam, PhD candidate now!

Publications

* denotes equal contribution or alphabetical order.

	AdaLLaVA: Learning to Inference Adaptively for Multimodal Large Language Models Zhuoyan Xu*, Khoi Duc Nguyen*, Preeti Mukherjee, Somali Chaterji, Saurabh Bagchi, Yingyu Liang, Yin Li [ Website ]
	TabRAG: Efficient Table Retrieval and Understanding with Large Multimodal Models Zhuoyan Xu, Haoyang Fang, Boran Han, Bonan Min, Bernie Wang, Shuai Zhang Work done during internship at AWS [ abstract ]
	Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers Yingyu Liang*, Heshan Liu*, Zhenmei Shi*, Zhao Song*, Zhuoyan Xu*, Junze Yin* arXiv, 2024 [ arXiv ]
	Out-of-distribution generalization via composition: a lens through induction heads in Transformers Jiajun Song, Zhuoyan Xu, Yiqiao Zhong arXiv, 2024 [ arXiv ] [ Code ]
	Do Large Language Models Have Compositional Ability? An Investigation into Limitations and Scalability Zhuoyan Xu*, Zhenmei Shi*, Yingyu Liang COLM (Conference on Language Modeling) 2024 [ OpenReview ] [ arXiv ] [ Code ] [ Poster ] [ Workshop ] [ Workshop Poster ] [ Workshop Slides ]
	AdaInf: Adaptive Inference for Resource-Constrained Foundation Models Zhuoyan Xu, Khoi Duc Nguyen, Preeti Mukherjee, Somali Chaterji, Yingyu Liang, Yin Li ICML 2024 Workshop [ OpenReview ] [ Poster ]
	Why Larger Language Models Do In-context Learning Differently? Zhenmei Shi, Junyi Wei, Zhuoyan Xu, Yingyu Liang ICML 2024 [ Openreview ] [ arXiv ] [ Poster ] [ Workshop ] [ Workshop Poster ]
	Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning Zhuoyan Xu, Zhenmei Shi, Junyi Wei, Fangzhou Mu, Yin Li, Yingyu Liang ICLR 2024 [ OpenReview ] [ arXiv ] [ Code ] [ IBM Research Talk Slides ] [ Poster ] [ Video ] [ Workshop ] [ Workshop Poster ] [ Workshop Slides ]
	Spatial Transcriptomics Dimensionality Reduction using Wavelet Bases Zhuoyan Xu, Kris Sankaran F1000, 2022 [ F1000 Research ] [ arXiv ] [ Rpackage ] [ code ]
	Generalized Tensor Regression with Covariates on Multiple Modes Zhuoyan Xu, Jiaxin Hu, Miaoyan Wang arXiv, 2019 [ arXiv ] [ Rpackage ]

Research & Work Experience

	Research Assistant University of Wisconsin-Madison 2022 - Now | Prof. Yingyu Liang and Prof. Yin Li 2023 - Now | Prof. Yiqiao Zhong 2021 - 2022 | Prof. Kris Sankaran
	Applied Scientist Intern Amazon AWS AI in Bellevue, WA Summer 2024 | Shuai Zhang , Boran Han and Haoyang Fang
	Machine Learning Engineer Intern John Deere in Fargo, ND Summer 2022 | Lav Thyagarrajan
	Data Scientist Intern China Merchants Bank in Shanghai, China Summer 2018

Academic Services

Conference Reviewer at ICML 2024-2025, NeurIPS 2024, ICLR 2025, AISTATS 2025, CVPR 2025

Teaching

Teaching Assistant:
STAT 371: Introductory Applied Statistics for the Life Sciences (20 Fall)
STAT 301: Introduction to Statistical Methods (21 Spring, 21 Summer)
STAT 303-305: R for Statistics (21 Fall)
STAT 479: Statistical Data Visualization (22 Spring)

Instructor of VISP Non-credit program:
Intro to Big Data (Jan. to Feb. in 2020) [ Slides1 ,  Slides2 ]

Misc

Prelim: [ Document ,  Slides ] This page has been accessed times since Jan 20, 2024
Last updated: Dec 17, 2024