Wu, Jiayun

12 publications

ICLR 2026 Dimension-Free Decision Calibration for Nonlinear Loss Functions Jingwu Tang, Jiayun Wu, Steven Wu, Jiahao Zhang

ICLR 2026 Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-Correction Yong Lin, Shange Tang, Bohan Lyu, Ziran Yang, Jui-Hui Chung, Haoyu Zhao, Lai Jiang, Yihan Geng, Jiawei Ge, Jingruo Sun, Jiayun Wu, Jiri Gesi, Ximing Lu, David Acuna, Kaiyu Yang, Hongzhou Lin, Yejin Choi, Danqi Chen, Sanjeev Arora, Chi Jin

ICLR 2025 Benign Overfitting in Out-of-Distribution Generalization of Linear Models Shange Tang, Jiayun Wu, Jianqing Fan, Chi Jin

ICML 2025 Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage Konstantina Bairaktari, Jiayun Wu, Steven Wu

ICML 2025 Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph Weihuang Zheng, Jiashuo Liu, Jiaxing Li, Jiayun Wu, Peng Cui, Youyong Kong

NeurIPSW 2024 Benign Overfitting in Out-of-Distribution Generalization of Linear Models Shange Tang, Jiayun Wu, Jianqing Fan, Chi Jin

NeurIPS 2024 Bridging Multicalibration and Out-of-Distribution Generalization Beyond Covariate Shift Jiayun Wu, Jiashuo Liu, Peng Cui, Zhiwei Steven Wu

AISTATS 2024 Enhancing Distributional Stability Among Sub-Populations Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui

ICML 2024 Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Bo Li, Peng Cui

NeurIPSW 2023 Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications Jiashuo Liu, Jiayun Wu, Tianyu Wang, Hao Zou, Peng Cui

ICLR 2023 Measure the Predictive Heterogeneity Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui

NeurIPS 2022 Distributionally Robust Optimization with Data Geometry Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui