Han Yu - RankMe

28 papers A* 10Journal 16Unranked 2

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	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
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`	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	A*	`conf`	Quantization Meets OOD: Generalizable Quantization-aware Training from a Flatness Perspective. ACM Multimedia Jiacheng Jiang, Yuan Meng, Chen Tang, Han Yu, Qun Li, Zhi Wang, Wenwu Zhu
2025	J	`jnl`	Quantization Meets OOD: Generalizable Quantization-aware Training from a Flatness Perspective. CoRR Jiacheng Jiang, Yuan Meng, Chen Tang, Han Yu, Qun Li, Zhi Wang, Wenwu Zhu
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	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`	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	J	`jnl`	GAQAT: gradient-adaptive quantization-aware training for domain generalization. CoRR Jiacheng Jiang, Yuan Meng, Chen Tang, Han Yu, Qun Li, Zhi Wang, Wenwu Zhu
2024	A*	`conf`	Rethinking the Evaluation Protocol of Domain Generalization. CVPR Han Yu, Xingxuan Zhang, Renzhe Xu, Jiashuo Liu, Yue He, 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	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	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	—	`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	J	`jnl`	Towards Out-Of-Distribution Generalization: A Survey. CoRR Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui