Xingxuan Zhang

60 papers A* 21A 1B 2Journal 33Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Knowledge-Informed Pretrained Model for Causal Discovery. CoRR Wenbo Xu, Yue He, Yunhai Wang, Xingxuan Zhang, Kun Kuang, Yueguo Chen, Peng Cui
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	A*	`conf`	Generating Risky Samples with Conformity Constraints via Diffusion Models. AAAI Han Yu, Hao Zou, Xingxuan Zhang, Zhengyi Wang, Yue He, Kehan Li, Peng Cui
2026	J	`jnl`	TFMLinker: Universal Link Predictor by Graph In-Context Learning with Tabular Foundation Models. CoRR Tianyin Liao, Chunyu Hu, Yicheng Sui, Xingxuan Zhang, Peng Cui, Jianxin Li, Ziwei Zhang
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	A	`conf`	Dynamic Model Fusion for Multi-Source Test-Time Adaptation. ECAI Yuan Xue, Qinting Jiang, Yuan Meng, Xingxuan Zhang, Chen Tang, Jingyan Jiang, Zhi Wang
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	J	`jnl`	Exploring and Exploiting Data Heterogeneity in Recommendation. ACM Trans. Knowl. Discov. Data Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui
2025	J	`jnl`	Generating Risky Samples with Conformity Constraints via Diffusion Models. CoRR Han Yu, Hao Zou, Xingxuan Zhang, Zhengyi Wang, Yue He, Kehan Li, Peng Cui
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`	ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction. CoRR Han Yu, Kehan Li, Dongbai Li, Yue He, Xingxuan Zhang, Peng Cui
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	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	J	`jnl`	A Survey on Evaluation of Out-of-Distribution Generalization. CoRR Han Yu, Jiashuo Liu, Xingxuan Zhang, Jiayun Wu, 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	A*	`conf`	Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection. NeurIPS Jieren Deng, Haojian Zhang, Kun Ding, Jianhua Hu, Xingxuan Zhang, Yunkuan Wang
2024	J	`jnl`	Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection. CoRR Jieren Deng, Haojian Zhang, Kun Ding, Jianhua Hu, Xingxuan Zhang, Yunkuan Wang
2023	J	`jnl`	Class Incremental Robotic Pick-and-Place via Incremental Few-Shot Object Detection. IEEE Robotics Autom. Lett. Jieren Deng, Haojian Zhang, Jianhua Hu, Xingxuan Zhang, Yunkuan Wang
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	J	`jnl`	Exploring and Exploiting Data Heterogeneity in Recommendation. CoRR Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, 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	—	`conf`	Learning Vector Quantized Shape Code for Amodal Blastomere Instance Segmentation. ISBI Won-Dong Jang, Donglai Wei, Xingxuan Zhang, Brian D. Leahy, Helen Y. Yang, James Tompkin, Dalit Ben-Yosef, Daniel Needleman, Hanspeter Pfister
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`	Meta Adaptive Task Sampling for Few-Domain Generalization. CoRR Zheyan Shen, Han Yu, Peng Cui, Jiashuo Liu, Xingxuan Zhang, Linjun Zhou, Furui Liu
2023	J	`jnl`	Motion Forecasting Network (MoFCNet): IMU-Based Human Motion Forecasting for Hip Assistive Exoskeleton. IEEE Robotics Autom. Lett. Xingxuan Zhang, Haojian Zhang, Jianhua Hu, Jieren Deng, Yunkuan Wang
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`	Qwen Technical Report. CoRR Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, Tianhang Zhu
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
2023	J	`jnl`	TouchStone: Evaluating Vision-Language Models by Language Models. CoRR Shuai Bai, Shusheng Yang, Jinze Bai, Peng Wang, Xingxuan Zhang, Junyang Lin, Xinggang Wang, Chang Zhou, Jingren Zhou
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`	Adversarial Eigen Attack on BlackBox Models. CVPR Linjun Zhou, Peng Cui, Xingxuan Zhang, Yinan Jiang, Shiqiang Yang
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	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	J	`jnl`	Learning Vector Quantized Shape Code for Amodal Blastomere Instance Segmentation. CoRR Won-Dong Jang, Donglai Wei, Xingxuan Zhang, Brian D. Leahy, Helen Y. Yang, James Tompkin, Dalit Ben-Yosef, Daniel Needleman, Hanspeter Pfister
2020	B	`conf`	Speaker-Independent Lipreading With Limited Data. ICIP Chenzhao Yang, Shilin Wang, Xingxuan Zhang, Yun Zhu
2019	A*	`conf`	Spatio-Temporal Fusion Based Convolutional Sequence Learning for Lip Reading. ICCV Xingxuan Zhang, Feng Cheng, Shilin Wang
2018	B	`conf`	3D Convolutional Neural Networks Based Speaker Identification and Authentication. ICIP Jianguo Liao, Shilin Wang, Xingxuan Zhang, Gongshen Liu