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ORCIDRenzhe Xu
Person information
- unicode name: 徐韧喆
- affiliation: Shanghai University of Finance and Economics, Institute for Theoretical Computer Science, China
- affiliation (PhD 2024): Tsinghua University, Department of Computer Science, Beijing, China
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2020 – today
- 2025
[c23]Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui:
COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. CVPR 2025: 9186-9198- [c22]Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Liping Jing, Peng Cui:
On the Out-Of-Distribution Generalization of Large Multimodal Models. CVPR 2025: 10315-10326 - [c21]Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui:
Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. ICLR 2025 - [i23]Han Yu, Jiashuo Liu, Hao Zou, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui:
Error Slice Discovery via Manifold Compactness. CoRR abs/2501.19032 (2025) - [i22]Han Yu, Yue He, Renzhe Xu, Dongbai Li, Jiayin Zhang, Wenchao Zou, Peng Cui:
Sample Weight Averaging for Stable Prediction. CoRR abs/2502.07414 (2025) - [i21]Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui:
Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. CoRR abs/2503.15579 (2025) - [i20]Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui:
COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. CoRR abs/2504.10158 (2025) - [i19]Renzhe Xu, Kang Wang, Bo Li:
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources. CoRR abs/2505.07688 (2025) - 2024
- [j1]Shaohua Fan, Renzhe Xu
, Qian Dong, Yue He, Cheng Chang, Peng Cui:
Stable Cox regression for survival analysis under distribution shifts. Nat. Mac. Intell. 6(12): 1525-1541 (2024) - [c20]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CVPR 2024: 21897-21908 - [c19]Yue He, Pengfei Tian, Renzhe Xu, Xinwei Shen, Xingxuan Zhang, Peng Cui:
Model-Agnostic Random Weighting for Out-of-Distribution Generalization. KDD 2024: 1050-1061 - [i18]Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Peng Cui:
On the Out-Of-Distribution Generalization of Multimodal Large Language Models. CoRR abs/2402.06599 (2024) - [i17]Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui:
PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators. CoRR abs/2403.15524 (2024) - [i16]Kamesh Munagala, Yiheng Shen, Renzhe Xu:
The Limits of Interval-Regulated Price Discrimination. CoRR abs/2406.06023 (2024) - 2023
- [c18]Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang:
Stable Learning via Sparse Variable Independence. AAAI 2023: 10998-11006 - [c17]Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui:
Covariate-Shift Generalization via Random Sample Weighting. AAAI 2023: 11828-11836 - [c16]Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui:
Factual Observation Based Heterogeneity Learning for Counterfactual Prediction. CLeaR 2023: 350-370 - [c15]Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui:
NICO++: Towards Better Benchmarking for Domain Generalization. CVPR 2023: 16036-16047 - [c14]Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui:
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CVPR 2023: 20247-20257 - [c13]Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui:
Flatness-Aware Minimization for Domain Generalization. ICCV 2023: 5166-5179 - [c12]Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui:
Measure the Predictive Heterogeneity. ICLR 2023 - [c11]Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui:
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. ICML 2023: 38674-38706 - [i15]Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang:
Model Agnostic Sample Reweighting for Out-of-Distribution Learning. CoRR abs/2301.09819 (2023) - [i14]Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui:
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CoRR abs/2303.03108 (2023) - [i13]Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui:
Rethinking the Evaluation Protocol of Domain Generalization. CoRR abs/2305.15253 (2023) - [i12]Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui:
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. CoRR abs/2305.19158 (2023) - [i11]Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui:
Flatness-Aware Minimization for Domain Generalization. CoRR abs/2307.11108 (2023) - 2022
- [c10]Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu:
Towards Unsupervised Domain Generalization. CVPR 2022: 4900-4910 - [c9]Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui:
NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges. ECCV Workshops (6) 2022: 433-450 - [c8]Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui:
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. ICML 2022: 24803-24829 - [c7]Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang:
Model Agnostic Sample Reweighting for Out-of-Distribution Learning. ICML 2022: 27203-27221 - [c6]Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui:
Product Ranking for Revenue Maximization with Multiple Purchases. NeurIPS 2022 - [c5]Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. WWW 2022: 4-15 - [i10]Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. CoRR abs/2202.04245 (2022) - [i9]Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, Chen Li:
Towards Domain Generalization in Object Detection. CoRR abs/2203.14387 (2022) - [i8]Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui:
NICO++: Towards Better Benchmarking for Domain Generalization. CoRR abs/2204.08040 (2022) - [i7]Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui:
Product Ranking for Revenue Maximization with Multiple Purchases. CoRR abs/2210.08268 (2022) - [i6]Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang:
Stable Learning via Sparse Variable Independence. CoRR abs/2212.00992 (2022) - 2021
- [c4]Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-of-Distribution Generalization. CVPR 2021: 5372-5382 - [c3]Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang:
DARING: Differentiable Causal Discovery with Residual Independence. KDD 2021: 596-605 - [i5]Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-Of-Distribution Generalization. CoRR abs/2104.07876 (2021) - [i4]Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu:
Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization. CoRR abs/2107.06219 (2021) - [i3]Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui:
Towards Out-Of-Distribution Generalization: A Survey. CoRR abs/2108.13624 (2021) - [i2]Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang:
Why Stable Learning Works? A Theory of Covariate Shift Generalization. CoRR abs/2111.02355 (2021) - 2020
- [c2]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. KDD 2020: 2125-2135 - [i1]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. CoRR abs/2006.10483 (2020)
2010 – 2019
Coauthor Index
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