Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks. - Gaotang Li; Marlena Duda; Xiang Zhang 012; Danai Koutra; Yujun Yan (KDD, 2023)

Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective. - Yujun Yan; Gaotang Li; Danai Koutra (CoRR, 2023)

On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks. - Jiong Zhu; Gaotang Li; Yao-An Yang; Jing Zhu 005; Xuehao Cui; Danai Koutra (NeurIPS, 2024)

Bias Amplification Enhances Minority Group Performance. - Gaotang Li; Jiarui Liu 004; Wei Hu (Trans. Mach. Learn. Res., 2024)

Taming Knowledge Conflicts in Language Models. - Gaotang Li; Yuzhong Chen; Hanghang Tong (CoRR, 2025)

RM-R1: Reward Modeling as Reasoning. - Xiusi Chen; Gaotang Li; Ziqi Wang 003; Bowen Jin; Cheng Qian 008; Yu Wang 072; Hongru Wang 011; Yu Zhang 044; Denghui Zhang; Tong Zhang 001; Hanghang Tong; Heng Ji 001 (CoRR, 2025)

MORALISE: A Structured Benchmark for Moral Alignment in Visual Language Models. - Xiao Lin; Zhining Liu 002; Ze Yang; Gaotang Li; Ruizhong Qiu; Shuke Wang; Hui Liu; Haotian Li; Sumit Keswani; Vishwa Pardeshi; Huijun Zhao; Wei Fan 001; et al. (CoRR, 2025)

Saffron-1: Towards an Inference Scaling Paradigm for LLM Safety Assurance. - Ruizhong Qiu; Gaotang Li; Tianxin Wei; Jingrui He; Hanghang Tong (CoRR, 2025)