Su, Weijie J.

20 publications

ICLR 2025 Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic Ruochen Jin, Bojian Hou, Jiancong Xiao, Weijie J Su, Li Shen

ICLR 2025 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

NeurIPS 2025 Mitigating the Privacy–Utility Trade-Off in Decentralized Federated Learning via F-Differential Privacy Xiang Li, Chendi Wang, Buxin Su, Qi Long, Weijie J Su

NeurIPS 2025 On the Empirical Power of Goodness-of-Fit Tests in Watermark Detection Weiqing He, Xiang Li, Tianqi Shang, Li Shen, Weijie J Su, Qi Long

JMLR 2025 Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers Fan Yang, Hongyang R. Zhang, Sen Wu, Christopher Re, Weijie J. Su

ICML 2025 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

ICMLW 2024 A Peek into Token Bias: Large Language Models Are Not yet Genuine Reasoners Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, Xiaomeng Wang, Tanwi Mallick, Weijie J Su, Camillo Jose Taylor, Dan Roth

ICMLW 2024 Multi-Modal and Multi-Agent Systems Meet Rationality: A Survey Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang, Weijie J Su, Camillo Jose Taylor, Tanwi Mallick

ICML 2024 Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-Perfect Representation Learning Chendi Wang, Yuqing Zhu, Weijie J Su, Yu-Xiang Wang

ICMLW 2024 Position Paper: Dual-System Language Models via Next-Action Prediction Zhehang Du, Weijie J Su

TMLR 2024 Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic Matteo Sordello, Niccolo Dalmasso, Hangfeng He, Weijie J Su

ICML 2024 Shifted Interpolation for Differential Privacy Jinho Bok, Weijie J Su, Jason Altschuler

ICLR 2023 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

JMLR 2023 HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation Weijie J. Su, Yuancheng Zhu

JMLR 2023 Minimax Estimation for Personalized Federated Learning: An Alternative Between FedAvg and Local Training? Shuxiao Chen, Qinqing Zheng, Qi Long, Weijie J. Su

ICMLW 2023 Reward Collapse in Aligning Large Language Models: A Prompt-Aware Approach to Preference Rankings Ziang Song, Tianle Cai, Jason D. Lee, Weijie J Su

ICML 2023 The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent Lei Wu, Weijie J Su

ICLR 2022 An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J Su

ICLR 2022 Weighted Training for Cross-Task Learning Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J Su

ICLR 2020 The Local Elasticity of Neural Networks Hangfeng He, Weijie J. Su