Fang, Zhen

31 publications

NeurIPS 2025 An Information-Theoretical Framework for Understanding Out-of-Distribution Detection with Pretrained Vision-Language Models Bo Peng, Jie Lu, Guangquan Zhang, Zhen Fang

ICLR 2025 Deep Kernel Relative Test for Machine-Generated Text Detection Yiliao Song, Zhenqiao Yuan, Shuhai Zhang, Zhen Fang, Jun Yu, Feng Liu

NeurIPS 2025 Learning Robust Spectral Dynamics for Temporal Domain Generalization En Yu, Jie Lu, Xiaoyu Yang, Guangquan Zhang, Zhen Fang

CVPR 2025 NLPrompt: Noise-Label Prompt Learning for Vision-Language Models Bikang Pan, Qun Li, Xiaoying Tang, Wei Huang, Zhen Fang, Feng Liu, Jingya Wang, Jingyi Yu, Ye Shi

ICCV 2025 On the Provable Importance of Gradients for Autonomous Language-Assisted Image Clustering Bo Peng, Jie Lu, Guangquan Zhang, Zhen Fang

NeurIPS 2025 Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents Zhizhen Zhang, Lei Zhu, Zhen Fang, Zi Huang, Yadan Luo

ICLR 2025 Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer Ningyuan Zhang, Jie Lu, Keqiuyin Li, Zhen Fang, Guangquan Zhang

ICML 2025 Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li

ICLRW 2025 Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li

ICLR 2024 ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang

ICLR 2024 How Does Unlabeled Data Provably Help Out-of-Distribution Detection? Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li

ICML 2024 Knowledge Distillation with Auxiliary Variable Bo Peng, Zhen Fang, Guangquan Zhang, Jie Lu

NeurIPS 2024 Learning to Shape In-Distribution Feature Space for Out-of-Distribution Detection Yonggang Zhang, Jie Lu, Bo Peng, Zhen Fang, Yiu-ming Cheung

ICLR 2024 Negative Label Guided OOD Detection with Pretrained Vision-Language Models Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

ICLR 2024 NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models Beyond Spherical Linear Interpolation PengFei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han

JMLR 2024 On the Learnability of Out-of-Distribution Detection Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu

ICLR 2024 Out-of-Distribution Detection with Negative Prompts Jun Nie, Yonggang Zhang, Zhen Fang, Tongliang Liu, Bo Han, Xinmei Tian

ICML 2023 Detecting Out-of-Distribution Data Through In-Distribution Class Prior Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

NeurIPS 2023 Invariant Learning via Probability of Sufficient and Necessary Causes Mengyue Yang, Zhen Fang, Yonggang Zhang, Yali Du, Furui Liu, Jean-Francois Ton, Jianhong Wang, Jun Wang

ICCV 2023 KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Mahsa Baktashmotlagh, Zi Huang

NeurIPS 2023 Learning to Augment Distributions for Out-of-Distribution Detection Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han

ICCV 2023 Meta OOD Learning for Continuously Adaptive OOD Detection Xinheng Wu, Jie Lu, Zhen Fang, Guangquan Zhang

ICML 2023 Moderately Distributional Exploration for Domain Generalization Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han, Xinmei Tian

NeurIPS 2023 Out-of-Distribution Detection Learning with Unreliable Out-of-Distribution Sources Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han

NeurIPS 2023 SODA: Robust Training of Test-Time Data Adaptors Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han

CVPR 2022 Federated Class-Incremental Learning Jiahua Dong, Lixu Wang, Zhen Fang, Gan Sun, Shichao Xu, Xiao Wang, Qi Zhu

NeurIPS 2022 Is Out-of-Distribution Detection Learnable? Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu

NeurIPS 2021 Confident Anchor-Induced Multi-Source Free Domain Adaptation Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu

AAAI 2021 How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches? Zhong Li, Zhen Fang, Feng Liu, Jie Lu, Bo Yuan, Guangquan Zhang

ICML 2021 Learning Bounds for Open-Set Learning Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang

IJCAI 2020 Clarinet: A One-Step Approach Towards Budget-Friendly Unsupervised Domain Adaptation Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu