Yue He - RankMe

46 papers A* 20Journal 24Unranked 2

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`	Contrastive Learning for Large-scale Color-Name Dataset: Tackling Sparsity with Negative Sampling. CHI Kecheng Lu, Yue He, Yunhai Wang
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	A*	`conf`	Invariant Learning on Heterogeneous Graphs via Subgraph Environment Inference. WWW Yanghui Fu, Yunfei Wang, Hao Zou, Yue He, Haotian Wang, Qing Cheng, Guangquan Cheng, Shixuan Liu
2025	J	`jnl`	AdaptSel: Adaptive Selection of Biased and Debiased Recommendation Models for Varying Test Environments. ACM Trans. Knowl. Discov. Data Zimu Wang, Hao Zou, Jiashuo Liu, Jiayun Wu, Pengfei Tian, Yue He, Peng Cui
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`	Environment Inference for Learning Generalizable Dynamical System. CoRR Shixuan Liu, Yue He, Haotian Wang, Wenjing Yang, Yunfei Wang, Peng Cui, Zhong Liu
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`	EvoPath: Evolutionary Meta-path Discovery with Large Language Models for Complex Heterogeneous Information Networks. CoRR Shixuan Liu, Haoxiang Cheng, Yunfei Wang, Yue He, Changjun Fan, Zhong Liu
2025	J	`jnl`	EvoPath: Evolutionary meta-path discovery with large language models for complex heterogeneous information networks. Inf. Process. Manag. Shixuan Liu, Haoxiang Cheng, Yunfei Wang, Yue He, Changjun Fan, Zhong Liu
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	—	`conf`	PDMC: Generating Feasible Algorithmic Recourse via Perturbation Data Manifold Constraint. KDD (2) Zimu Wang, Hao Zou, Han Yu, Shaohua Fan, Haotian Wang, Yue He, Peng Cui
2025	J	`jnl`	Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift. CoRR Shixuan Liu, Yue He, Yunfei Wang, Hao Zou, Haoxiang Cheng, Wenjing Yang, Peng Cui, Zhong Liu
2025	J	`jnl`	Sample Weight Averaging for Stable Prediction. CoRR Han Yu, Yue He, Renzhe Xu, Dongbai Li, Jiayin Zhang, Wenchao Zou, Peng Cui
2024	A*	`conf`	Domain-wise Data Acquisition to Improve Performance under Distribution Shift. ICML Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu, Hao Zou, 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	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
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	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`	MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters. ICCV Min Zhang, Junkun Yuan, Yue He, Wenbin Li, Zhengyu Chen, Kun Kuang
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`	CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. WWW Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang
2022	J	`jnl`	CausPref: Causal Preference Learning for Out-of-Distribution Recommendation. CoRR Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang
2022	J	`jnl`	Distilling Causal Metaknowledge from Knowledge Graphs. IEEE Data Eng. Bull. Yuan Meng, Yancheng Dong, Shixuan Liu, Chaohao Yuan, Yue He, Jian Pei, Peng Cui
2022	A*	`conf`	Invariant Preference Learning for General Debiasing in Recommendation. KDD Zimu Wang, Yue He, Jiashuo Liu, Wenchao Zou, Philip S. Yu, Peng Cui
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	J	`jnl`	Stable Learning via Sparse Variable Independence. CoRR Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang
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	A*	`conf`	Purify and Generate: Learning Faithful Item-to-Item Graph from Noisy User-Item Interaction Behaviors. KDD Yue He, Yancheng Dong, Peng Cui, Yuhang Jiao, Xiaowei Wang, Ji Liu, Philip S. Yu
2021	J	`jnl`	Towards Non-I.I.D. image classification: A dataset and baselines. Pattern Recognit. Yue He, Zheyan Shen, Peng Cui
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
2020	A*	`conf`	Counterfactual Prediction for Bundle Treatment. NeurIPS Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He
2020	A*	`conf`	Learning Stable Graphs from Multiple Environments with Selection Bias. KDD Yue He, Peng Cui, Jianxin Ma, Hao Zou, Xiaowei Wang, Hongxia Yang, Philip S. Yu
2019	J	`jnl`	NICO: A Dataset Towards Non-I.I.D. Image Classification. CoRR Yue He, Zheyan Shen, Peng Cui
2018	A*	`conf`	Progressive Generative Hashing for Image Retrieval. IJCAI Yuqing Ma, Yue He, Fan Ding, Sheng Hu, Jun Li, Xianglong Liu