Y. Zhang, J. Lu, B. Peng, Z. Fang, Y.M. Cheung.
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection.
In Conference on Neural Information Processing Systems (NeurIPS 2024), Published Online, 2024.
[ Link ] [ CODE ]

Z. Tang, Y. Zhang, P. Dong, Y.M. Cheung, A.C. Zhou, B. Han, X. Chu.
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion.
In Conference on Neural Information Processing Systems (NeurIPS 2024) (Spotlight), Published Online, 2024.
[ Link ] [ CODE ]

W. Zhang, C. Wan, Y. Zhang^†, Y.M. Cheung, X. Tian, X. Shen^†, J. Ye.
Interpreting and Improving Large Language Models in Arithmetic Calculation.
In International Conference on Machine Learning (ICML 2024) (Oral), Published Online, 2024 .
[ Link ] [ CODE ]

Y. Zhang, Z. Yang, X. Tian, N. Wang, T. Liu, B. Han.
Robust Training of Federated Models with Extremely Label Deficiency.
In International Conference on Learning Representations (ICLR 2024), Published Online, 2024 .
[ Link ] [ CODE ]

P. Zheng*, Y. Zhang*, Z. Fang, T. Liu, D. Lian, B. Han.
Beyond Linear Spherical Interpolation: Noise Correction for Image Interpolation with Diffusion Models.
In International Conference on Learning Representations (ICLR 2024) (Spotlight), Published Online, 2024 .
[ Link ] [ CODE ]

J. Nie, Y. Zhang^†, Z. Fang, T. Liu, B. Han, X. Tian^†.
Out-of-Distribution Detection with Negative Prompts.
In International Conference on Learning Representations (ICLR 2024), Published Online, 2024 .
[ Link ] [ CODE ]

R. Dai, Y. Zhang, A. Li, T. Liu, X. Yang, B. Han.
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting.
In International Conference on Learning Representations (ICLR 2024), Published Online, 2024 .
[ Link ] [ CODE ]

Z. Tang, Y. Zhang, S.Shi, X. Tian, T. Liu, B. Han, X. Chu.
FedImpro: Measuring and Improving Client Update in Federated Learning.
In International Conference on Learning Representations (ICLR 2024), Published Online, 2024 .
[ Link ] [ CODE ]

Z. Yang*, Y. Zhang*, Y. Zheng, X. Tian, H. Peng, T. Liu, B. Han.
FedFed: Feature Distillation against Data Heterogeneity in Federated.
In Conference on Neural Information Processing Systems (NeurIPS 2023), Published Online, 2023 .
[ Link ] [ CODE ]

M. Yang, Z. Fang, Y. Zhang^†, Y. Du, F. Liu, J.F Ton, J. Wang^†.
Invariant Learning via Probability of Sufficient and Necessary Causes.
In Conference on Neural Information Processing Systems (NeurIPS 2023) (Spotlight), Published Online, 2023 .
[ Link ] [ CODE ] [ Spotlight ]

R. Dai, Y. Zhang^†, Z. Fang, B. Han, X. Tian^†.
Moderately Distributional Exploration for Domain Generalization.
In International Conference on Machine Learning (ICML 2023), Published Online, 2023 .
[ Link ] [ CODE ]

C. Sun, Y. Zhang, W. Chaoqun, Q. Wang, Y. Li, T. Liu, B. Han, X. Tian.
Towards Lightweight Black-Box Attacks against Deep Neural Networks.
In Conference on Neural Information Processing Systems (NeurIPS 2022), Published Online, 2022 .
[ Link ] [ CODE ]

Y. Chen, Y. Zhang, H. Yang, K. Ma, B. Xie, T. Liu, B. Han, J. Cheng.
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.
In Conference on Neural Information Processing Systems (NeurIPS 2022), Published Online, 2022 .
[ Link ] [ CODE ] [ Spotlight ]

Z. Tang*, Y. Zhang*, S. Shi, X. He, B. Han, X. Chu.
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
In International Conference on Machine Learning (ICML 2022), Published Online, 2022 .
[ arXiv ] [ CODE ]

Y. Zhang, M. Gong, T. Liu, G. Niu, X. Tian, B. Han, B. Schölkopf, K. Zhang.
CausalAdv: Adversarial Robustness Through the Lens of Causality.
In International Conference on Learning Representations (ICLR 2022), Published Online, 2022 .
[ Link ] [ CODE ]

Y. Zhang, Y. Li, T. Liu, X. Tian.
Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks.
In International Conference on Machine Learning (ICML 2020), Published Online, 2020 .
[ Link ]

Y. Zhang, X. Tian
Consistent Prompt Learning for Vision-language Models.
Knowledge-Based Systems, 2025.
[ Link ]