Renzhe Xu - RankMe

54 papers A* 24Journal 26Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Error Slice Discovery via Manifold Compactness. AAAI Han Yu, Hao Zou, Jiashuo Liu, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui
2026	—	`conf`	Lower Bias, Higher Welfare: How Creator Competition Reshapes Bias-Variance Tradeoff in Recommendation Platforms? KDD (1) Kang Wang, Renzhe Xu, Bo Li
2026	A*	`conf`	Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents. AAAI Xinpeng Lv, Chunyuan Zheng, Yunxin Mao, Renzhe Xu, Hao Zou, Shanzhi Gu, Liyang Xu, Huan Chen, Yuanlong Chen, Wenjing Yang, Haotian Wang
2025	A*	`conf`	COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. CVPR Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui
2025	J	`jnl`	COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. CoRR Jiansheng Li, Xingxuan Zhang, Hao Zou, Yige Guo, Renzhe Xu, Yilong Liu, Chuzhao Zhu, Yue He, Peng Cui
2025	J	`jnl`	Error Slice Discovery via Manifold Compactness. CoRR Han Yu, Jiashuo Liu, Hao Zou, Renzhe Xu, Yue He, Xingxuan Zhang, Peng Cui
2025	A*	`conf`	Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources. ICML Renzhe Xu, Kang Wang, Bo Li
2025	J	`jnl`	Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources. CoRR Renzhe Xu, Kang Wang, Bo Li
2025	J	`jnl`	LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence. CoRR 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
2025	J	`jnl`	Lower Bias, Higher Welfare: How Creator Competition Reshapes Bias-Variance Tradeoff in Recommendation Platforms? CoRR Kang Wang, Renzhe Xu, Bo Li
2025	A*	`conf`	On the Out-Of-Distribution Generalization of Large Multimodal Models. CVPR Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Liping Jing, Peng Cui
2025	—	`conf`	PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators. KDD (2) Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui
2025	J	`jnl`	Sample Weight Averaging for Stable Prediction. CoRR Han Yu, Yue He, Renzhe Xu, Dongbai Li, Jiayin Zhang, Wenchao Zou, Peng Cui
2025	A*	`conf`	Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. ICLR Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui
2025	J	`jnl`	Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. CoRR Xingxuan Zhang, Haoran Wang, Jiansheng Li, Yuan Xue, Shikai Guan, Renzhe Xu, Hao Zou, Han Yu, Peng Cui
2024	A*	`conf`	Model-Agnostic Random Weighting for Out-of-Distribution Generalization. KDD Yue He, Pengfei Tian, Renzhe Xu, Xinwei Shen, Xingxuan Zhang, Peng Cui
2024	J	`jnl`	On the Out-Of-Distribution Generalization of Multimodal Large Language Models. CoRR Xingxuan Zhang, Jiansheng Li, Wenjing Chu, Junjia Hai, Renzhe Xu, Yuqing Yang, Shikai Guan, Jiazheng Xu, Peng Cui
2024	J	`jnl`	PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators. CoRR Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui
2024	A*	`conf`	Rethinking the Evaluation Protocol of Domain Generalization. CVPR Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui
2024	J	`jnl`	Stable Cox regression for survival analysis under distribution shifts. Nat. Mac. Intell. Shaohua Fan, Renzhe Xu, Qian Dong, Yue He, Cheng Chang, Peng Cui
2024	J	`jnl`	The Limits of Interval-Regulated Price Discrimination. CoRR Kamesh Munagala, Yiheng Shen, Renzhe Xu
2023	A*	`conf`	Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. ICML Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui
2023	J	`jnl`	Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. CoRR Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui
2023	A*	`conf`	Covariate-Shift Generalization via Random Sample Weighting. AAAI Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui
2023	—	`conf`	Factual Observation Based Heterogeneity Learning for Counterfactual Prediction. CLeaR Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui
2023	A*	`conf`	Flatness-Aware Minimization for Domain Generalization. ICCV Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui
2023	J	`jnl`	Flatness-Aware Minimization for Domain Generalization. CoRR Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui
2023	A*	`conf`	Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CVPR Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui
2023	J	`jnl`	Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. CoRR Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui
2023	A*	`conf`	Measure the Predictive Heterogeneity. ICLR Jiashuo Liu, Jiayun Wu, Renjie Pi, Renzhe Xu, Xingxuan Zhang, Bo Li, Peng Cui
2023	J	`jnl`	Model Agnostic Sample Reweighting for Out-of-Distribution Learning. CoRR Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang
2023	A*	`conf`	NICO++: Towards Better Benchmarking for Domain Generalization. CVPR Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui
2023	J	`jnl`	Rethinking the Evaluation Protocol of Domain Generalization. CoRR Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui
2023	A*	`conf`	Stable Learning via Sparse Variable Independence. AAAI Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang
2022	A*	`conf`	A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. ICML Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui
2022	A*	`conf`	Model Agnostic Sample Reweighting for Out-of-Distribution Learning. ICML Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang
2022	—	`conf`	NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges. ECCV Workshops (6) Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui
2022	J	`jnl`	NICO++: Towards Better Benchmarking for Domain Generalization. CoRR Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui
2022	A*	`conf`	Product Ranking for Revenue Maximization with Multiple Purchases. NeurIPS Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui
2022	J	`jnl`	Product Ranking for Revenue Maximization with Multiple Purchases. CoRR Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui
2022	A*	`conf`	Regulatory Instruments for Fair Personalized Pricing. WWW Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu
2022	J	`jnl`	Regulatory Instruments for Fair Personalized Pricing. CoRR Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu
2022	J	`jnl`	Stable Learning via Sparse Variable Independence. CoRR Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang
2022	J	`jnl`	Towards Domain Generalization in Object Detection. CoRR Xingxuan Zhang, Zekai Xu, Renzhe Xu, Jiashuo Liu, Peng Cui, Weitao Wan, Chong Sun, Chen Li
2022	A*	`conf`	Towards Unsupervised Domain Generalization. CVPR Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu
2021	A*	`conf`	DARING: Differentiable Causal Discovery with Residual Independence. KDD Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang
2021	J	`jnl`	Deep Stable Learning for Out-Of-Distribution Generalization. CoRR Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen
2021	A*	`conf`	Deep Stable Learning for Out-of-Distribution Generalization. CVPR Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen
2021	J	`jnl`	Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization. CoRR Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu
2021	J	`jnl`	Towards Out-Of-Distribution Generalization: A Survey. CoRR Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui
2021	J	`jnl`	Why Stable Learning Works? A Theory of Covariate Shift Generalization. CoRR Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang
2020	A*	`conf`	Algorithmic Decision Making with Conditional Fairness. KDD Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui
2020	J	`jnl`	Algorithmic Decision Making with Conditional Fairness. CoRR Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui
2019	A*	`conf`	Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena. KDD Yunfei Lu, Linyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, Wenwu Zhu