Renzhe Xu

According to our database, Renzhe Xu authored at least 35 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence.

Xingxuan Zhang, Gang Ren, Han Yu, Hao Yuan, Hui Wang, Jiansheng Li, Jiayun Wu, Lang Mo, Li Mao, Mingchao Hao, Ningbo Dai, Renzhe Xu, Shuyang Li, Tianyang Zhang, Yue He, Yuanrui Wang, Yunjia Zhang, Zijing Xu, Dongzhe Li, Fang Gao, Hao Zou, Jiandong Liu, Jiashuo Liu, Jiawei Xu, Kaijie Cheng, Kehan Li, Linjun Zhou, Qing Li, Shaohua Fan, Xiaoyu Lin, Xinyan Han, Xuanyue Li, Yan Lu, Yuan Xue, Yuanyuan Jiang, Zimu Wang, Zhenlei Wang, Peng Cui

CoRR, September, 2025

Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources.

Renzhe Xu, Kang Wang, Bo Li

CoRR, May, 2025

Sample Weight Averaging for Stable Prediction.

Han Yu, Yue He, Renzhe Xu, Dongbai Li, Jiayin Zhang, Wenchao Zou, Peng Cui

CoRR, February, 2025

Error Slice Discovery via Manifold Compactness.

Han Yu, Jiashuo Liu, Hao Zou, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui

CoRR, January, 2025

Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study.

Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

On the Out-Of-Distribution Generalization of Large Multimodal Models.

Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Liping Jing, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts.

Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Stable Cox regression for survival analysis under distribution shifts.

Shaohua Fan, Renzhe Xu, Qian Dong, Yue He, Cheng Chang, Peng Cui

Nat. Mac. Intell., 2024

The Limits of Interval-Regulated Price Discrimination.

Kamesh Munagala, Yiheng Shen, Renzhe Xu

CoRR, 2024

PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators.

Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui

CoRR, 2024

On the Out-Of-Distribution Generalization of Multimodal Large Language Models.

Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Peng Cui

CoRR, 2024

Model-Agnostic Random Weighting for Out-of-Distribution Generalization.

Yue He, Pengfei Tian, Renzhe Xu, Xinwei Shen, Xingxuan Zhang, Peng Cui

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Rethinking the Evaluation Protocol of Domain Generalization.

Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Competing for Shareable Arms in Multi-Player Multi-Armed Bandits.

Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui

Proceedings of the International Conference on Machine Learning, 2023

Measure the Predictive Heterogeneity.

Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Flatness-Aware Minimization for Domain Generalization.

Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization.

Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NICO++: Towards Better Benchmarking for Domain Generalization.

Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Factual Observation Based Heterogeneity Learning for Counterfactual Prediction.

Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Stable Learning via Sparse Variable Independence.

Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Covariate-Shift Generalization via Random Sample Weighting.

Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Towards Domain Generalization in Object Detection.

Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, Chen Li

CoRR, 2022

Regulatory Instruments for Fair Personalized Pricing.

Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Product Ranking for Revenue Maximization with Multiple Purchases.

Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Model Agnostic Sample Reweighting for Out-of-Distribution Learning.

Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang

Proceedings of the International Conference on Machine Learning, 2022

A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization.

Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui

Proceedings of the International Conference on Machine Learning, 2022

NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges.

Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Towards Unsupervised Domain Generalization.

Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Why Stable Learning Works? A Theory of Covariate Shift Generalization.

Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang

CoRR, 2021

Towards Out-Of-Distribution Generalization: A Survey.

Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui

CoRR, 2021

Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization.

Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

CoRR, 2021

DARING: Differentiable Causal Discovery with Residual Independence.

Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Deep Stable Learning for Out-of-Distribution Generalization.

Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Algorithmic Decision Making with Conditional Fairness.

Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena.

Yunfei Lu, Linyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, Wenwu Zhu

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019