Cui, Peng

71 publications

CVPR 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

MLJ 2025 Deep Sub-Ensembles Meets Quantile Regression: Uncertainty-Aware Imputation for Time Series Ying Liu, Peng Cui, Wenbo Hu, Richang Hong

NeurIPS 2025 Environment Inference for Learning Generalizable Dynamical System Shixuan Liu, Yue He, Haotian Wang, Wenjing Yang, Yunfei Wang, Peng Cui, Zhong Liu

ICLR 2025 Going Beyond Static: Understanding Shifts with Time-Series Attribution Jiashuo Liu, Nabeel Seedat, Peng Cui, Mihaela van der Schaar

CVPR 2025 Improving Accuracy and Calibration via Differentiated Deep Mutual Learning Han Liu, Peng Cui, Bingning Wang, Weipeng Chen, Yupeng Zhang, Jun Zhu, Xiaolin Hu

ICCV 2025 ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction Han Yu, Kehan Li, Dongbai Li, Yue He, Xingxuan Zhang, Peng Cui

CVPR 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

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

ICLR 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

ICLRW 2024 Agents: An Open-Source Framework for Autonomous Language Agents Wangchunshu Zhou, Yuchen Eleanor Jiang, Long Li, Jialong Wu, Tiannan Wang, Shuai Wang, Jiamin Chen, Jintian Zhang, Jing Chen, Xiangru Tang, Peng Cui, Ningyu Zhang, Huajun Chen, Mrinmaya Sachan

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

ICLR 2024 Debiased Collaborative Filtering with Kernel-Based Causal Balancing Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui

ICML 2024 Domain-Wise Data Acquisition to Improve Performance Under Distribution Shift Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu, Hao Zou, Peng Cui

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

CVPR 2024 Rethinking the Evaluation Protocol of Domain Generalization Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, Peng Cui

ICML 2024 Stability Evaluation Through Distributional Perturbation Analysis Jose Blanchet, Peng Cui, Jiajin Li, Jiashuo Liu

NeurIPSW 2024 Stability Evaluation of Large Language Models via Distributional Perturbation Analysis Jiashuo Liu, Jiajin Li, Peng Cui, Jose Blanchet

ICML 2023 Competing for Shareable Arms in Multi-Player Multi-Armed Bandits Renzhe Xu, Haotian Wang, Xingxuan Zhang, Bo Li, Peng Cui

AAAI 2023 Covariate-Shift Generalization via Random Sample Weighting Yue He, Xinwei Shen, Renzhe Xu, Tong Zhang, Yong Jiang, Wenchao Zou, Peng Cui

CLeaR 2023 Factual Observation Based Heterogeneity Learning for Counterfactual Prediction Hao Zou, Haotian Wang, Renzhe Xu, Bo Li, Jian Pei, Ye Jun Jian, Peng Cui

ICCV 2023 Flatness-Aware Minimization for Domain Generalization Xingxuan Zhang, Renzhe Xu, Han Yu, Yancheng Dong, Pengfei Tian, Peng Cui

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

CVPR 2023 Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization Xingxuan Zhang, Renzhe Xu, Han Yu, Hao Zou, Peng Cui

MLJ 2023 Heterogeneous Multi-Task Gaussian Cox Processes Feng Zhou, Quyu Kong, Zhijie Deng, Fengxiang He, Peng Cui, Jun Zhu

NeurIPS 2023 Learning Sample Difficulty from Pre-Trained Models for Reliable Prediction Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu

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

CVPR 2023 NICO++: Towards Better Benchmarking for Domain Generalization Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui

NeurIPS 2023 On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets Jiashuo Liu, Tianyu Wang, Peng Cui, Hongseok Namkoong

ICML 2023 Propensity Matters: Measuring and Enhancing Balancing for Recommendation Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, Peng Cui

ICML 2023 Provably Invariant Learning Without Domain Information Xiaoyu Tan, Lin Yong, Shengyu Zhu, Chao Qu, Xihe Qiu, Xu Yinghui, Peng Cui, Yuan Qi

AAAI 2023 Stable Learning via Sparse Variable Independence Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang

NeurIPS 2023 Towards Accelerated Model Training via Bayesian Data Selection Zhijie Deng, Peng Cui, Jun Zhu

ICML 2022 A Theoretical Analysis on Independence-Driven Importance Weighting for Covariate-Shift Generalization Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui

CVPR 2022 Adversarial Eigen Attack on Black-Box Models Linjun Zhou, Peng Cui, Xingxuan Zhang, Yinan Jiang, Shiqiang Yang

NeurIPS 2022 Confidence-Based Reliable Learning Under Dual Noises Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu

ICML 2022 Counterfactual Prediction for Outcome-Oriented Treatments Hao Zou, Bo Li, Jiangang Han, Shuiping Chen, Xuetao Ding, Peng Cui

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

ICML 2022 Model Agnostic Sample Reweighting for Out-of-Distribution Learning Xiao Zhou, Yong Lin, Renjie Pi, Weizhong Zhang, Renzhe Xu, Peng Cui, Tong Zhang

ECCVW 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

NeurIPS 2022 Product Ranking for Revenue Maximization with Multiple Purchases Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui

CVPR 2022 Towards Unsupervised Domain Generalization Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

NeurIPS 2022 ZIN: When and How to Learn Invariance Without Environment Partition? Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui

CVPR 2021 Deep Stable Learning for Out-of-Distribution Generalization Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen

ICML 2021 Heterogeneous Risk Minimization Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen

NeurIPS 2021 Integrated Latent Heterogeneity and Invariance Learning in Kernel Space Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen

AAAI 2021 Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation Kai Wang, Zhene Zou, Qilin Deng, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen, Peng Cui

AAAI 2021 Stable Adversarial Learning Under Distributional Shifts Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin

AAAI 2020 A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, Junzhou Huang

NeurIPS 2020 Calibrated Reliable Regression Using Maximum Mean Discrepancy Peng Cui, Wenbo Hu, Jun Zhu

NeurIPS 2020 Counterfactual Prediction for Bundle Treatment Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He

AAAI 2020 Rule-Guided Compositional Representation Learning on Knowledge Graphs Guanglin Niu, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, Xiaowei Zhang

AAAI 2020 Stable Learning via Sample Reweighting Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang

AAAI 2020 Stable Prediction with Model Misspecification and Agnostic Distribution Shift Kun Kuang, Ruoxuan Xiong, Peng Cui, Susan Athey, Bo Li

ICML 2019 Disentangled Graph Convolutional Networks Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, Wenwu Zhu

IJCAI 2019 Disparity-Preserved Deep Cross-Platform Association for Cross-Platform Video Recommendation Shengze Yu, Xin Wang, Wenwu Zhu, Peng Cui, Jingdong Wang

AAAI 2019 Incorporating Network Embedding into Markov Random Field for Better Community Detection Di Jin, Xinxin You, Weihao Li, Dongxiao He, Peng Cui, Françoise Fogelman-Soulié, Tanmoy Chakraborty

NeurIPS 2019 Learning Disentangled Representations for Recommendation Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yang, Wenwu Zhu

AAAI 2018 Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation Daixin Wang, Peng Cui, Wenwu Zhu

AAAI 2018 DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks Jianxin Ma, Peng Cui, Wenwu Zhu

IJCAI 2018 Power-Law Distribution Aware Trust Prediction Xiao Wang, Ziwei Zhang, Jing Wang, Peng Cui, Shiqiang Yang

AAAI 2018 Structural Deep Embedding for Hyper-Networks Ke Tu, Peng Cui, Xiao Wang, Fei Wang, Wenwu Zhu

AAAI 2018 TIMERS: Error-Bounded SVD Restart on Dynamic Networks Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, Wenwu Zhu

AAAI 2017 Community Preserving Network Embedding Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, Shiqiang Yang

AAAI 2017 Treatment Effect Estimation with Data-Driven Variable Decomposition Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang, Fei Wang

AAAI 2016 Little Is Much: Bridging Cross-Platform Behaviors Through Overlapped Crowds Meng Jiang, Peng Cui, Nicholas Jing Yuan, Xing Xie, Shiqiang Yang

IJCAI 2015 Deep Multimodal Hashing with Orthogonal Regularization Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu

AAAI 2015 Perceiving Group Themes from Collective Social and Behavioral Information Peng Cui, Tianyang Zhang, Fei Wang, Peng He

AAAI 2015 Probabilistic Attributed Hashing Mingdong Ou, Peng Cui, Jun Wang, Fei Wang, Wenwu Zhu

AAAI 2011 Item-Level Social Influence Prediction with Probabilistic Hybrid Factor Matrix Factorization Peng Cui, Fei Wang, Shiqiang Yang, Lifeng Sun

CVPR 2007 A Sequential Monte Carlo Approach to Anomaly Detection in Tracking Visual Events Peng Cui, Lifeng Sun, Zhi-Qiang Liu, Shiqiang Yang