About Me

I’m a first-year PhD student in Computer Science at University of Illinois Urbana-Champaign, working under the supervision of Hanghang Tong. Prior to this, I earned my bachelor’s degree from the University of Michigan. My main research lie broadly in large language models (LLMs), particularly developing the science of Language Models and enhancing their reasoning abilities. My current research interest is reasoning, RL, and alignment.

Email: gaotang3 [at] illinois [dot] edu

You can call me as Oliver. If you would like to chat with me about anything (e.g. research, internship opportunities, grad school application, mentorship etc.), feel free to submit this form.

Papers

(* denotes equal contribution)

• Saffron-1: Towards an Inference Scaling Paradigm for LLM Safety Assurance
  Ruizhong Qiu*, Gaotang Li*, Tianxin Wei, Jingrui He, Hanghang Tong
  Manuscript 2025
  [PDF] [Code] [Project Page] [Tweet]
  

• MORALISE: A Structured Benchmark for Moral Alignment in Visual Language Models
  Xiao Lin*, Zhining Liu*, Ze Yang*, Gaotang Li, Ruizhong Qiu, Shuke Wang, Hui Liu, Haotian Li, Sumit Keswani, Vishwa Pardeshi, Huijun Zhao, Wei Fan, Hanghang Tong
  Manuscript 2025
  [PDF] [HuggingFace]
  

• RM-R1: Reward Modeling as Reasoning
  Xiusi Chen*, Gaotang Li*, Ziqi Wang*, Bowen Jin, Cheng Qian, Yu Wang, Hongru Wang, Yu Zhang, Denghui Zhang, Tong Zhang, Hanghang Tong, Heng Ji
  Manuscript 2025
  [PDF] [Code] [HuggingFace] [Project Page] [Tweet]
  

• Taming Knowledge Conflicts in Language Models
  Gaotang Li, Yuzhong Chen, Hanghang Tong
  ICML 2025 (spotlight)
  [PDF] [Code] [HuggingFace] [Project Page] [Tweet]
  

Before Ph.D.

• On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
  Jiong Zhu*, Gaotang Li*, Yao-An Yang, Jing Zhu, Xuehao Cui, Danai Koutra
  NeurIPS 2024
  [PDF] [Code]
  

• Bias Amplification Enhances Minority Group Performance
  Gaotang Li*, Jiarui Liu*, Wei Hu
  TMLR 2024
  [PDF] [Code]
  

• Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective
  Gaotang Li, Danai Koutra, Yujun Yan
  KDD 2025
  [PDF] [Code]
  

• Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks
  Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan
  KDD 2023
  [PDF] [Code]