| 2026 | ACL | UCS: Estimating Unseen Coverage for Improved In-Context Learning. | Jiayi Xin, Xiang Li, Evan Qiang, Weiqing He, Tianqi Shang, Weijie J. Su, Qi Long |
| 2025 | ICLR | Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic. | Ruochen Jin, Bojian Hou, Jiancong Xiao, Weijie J. Su, Li Shen |
| 2025 | ICLR | Magnetic Preference Optimization: Achieving Last-iterate Convergence for Language Model Alignment. | Mingzhi Wang, Chengdong Ma, Qizhi Chen, Linjian Meng, Yang Han, Jiancong Xiao, Zhaowei Zhang, Jing Huo, Weijie J. Su, Yaodong Yang |
| 2025 | ICML | Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach. | Jiancong Xiao, Bojian Hou, Zhanliang Wang, Ruochen Jin, Qi Long, Weijie J. Su, Li Shen |
| 2025 | NAACL | Towards Rationality in Language and Multimodal Agents: A Survey. | Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang, Yuan Yuan, Zhuoqun Hao, Xinyi Bai, Weijie J. Su, Camillo Jose Taylor, Tanwi Mallick |
| 2024 | ICML | Shifted Interpolation for Differential Privacy. | Jinho Bok, Weijie J. Su, Jason M. Altschuler |
| 2024 | ICML | Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning. | Chendi Wang, Yuqing Zhu, Weijie J. Su, Yu-Xiang Wang |
| 2023 | ICLR | FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. | Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou |
| 2023 | ICML | The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent. | Lei Wu, Weijie J. Su |
| 2022 | ICLR | Weighted Training for Cross-Task Learning. | Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J. Su |
| 2022 | ICLR | An Unconstrained Layer-Peeled Perspective on Neural Collapse. | Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su |
| 2022 | ICML | ROCK: Causal Inference Principles for Reasoning about Commonsense Causality. | Jiayao Zhang, Hongming Zhang, Weijie J. Su, Dan Roth |
| 2021 | AISTATS | Federated f-Differential Privacy. | Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie J. Su |
| 2021 | ICML | Toward Better Generalization Bounds with Locally Elastic Stability. | Zhun Deng, Hangfeng He, Weijie J. Su |
| 2021 | ICML | Oneshot Differentially Private Top-k Selection. | Gang Qiao, Weijie J. Su, Li Zhang |
| 2020 | ICLR | The Local Elasticity of Neural Networks. | Hangfeng He, Weijie J. Su |
| 2020 | ICML | Towards Understanding the Dynamics of the First-Order Adversaries. | Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su |
| 2020 | ICML | Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. | Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su |