Zhen Fang

91 papers A* 30B 4C 1Journal 51Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Cross-domain Few-shot Classification via Invariant-content Feature Reconstruction.
Int. J. Comput. Vis.
Hongduan Tian, Feng Liu, Ka Chun Cheung, Zhen Fang, Simon See, Tongliang Liu, Bo Han
2026 — conf
Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models.
KDD (1)
Bo Peng, Jie Lu, Guangquan Zhang, Zhen Fang
2026 J jnl
How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability.
CoRR
Shawn Im, Changdae Oh, Zhen Fang, Sharon Li
2025 J jnl
Characterizing Submanifold Region for Out-of-Distribution Detection.
IEEE Trans. Knowl. Data Eng.
Xuhui Li, Zhen Fang, Yonggang Zhang, Ning Ma, Jiajun Bu, Bo Han, Haishuai Wang
2025 A* conf
Characterizing Submanifold Region for Out-of-Distribution Detection: (Extended Abstract).
ICDE
Xuhui Li, Zhen Fang, Yonggang Zhang, Ning Ma, Jiajun Bu, Bo Han, Haishuai Wang
2025 A* conf
Deep Kernel Relative Test for Machine-generated Text Detection.
ICLR
Yiliao Song, Zhenqiao Yuan, Shuhai Zhang, Zhen Fang, Jun Yu, Feng Liu
2025 — conf
Distributional Prototype Learning for Out-of-distribution Detection.
KDD (1)
Bo Peng, Jie Lu, Yonggang Zhang, Guangquan Zhang, Zhen Fang
2025 J jnl
Integrated Image-Text Augmentation for Few-Shot Learning in Vision-Language Models.
ACM Trans. Intell. Syst. Technol.
Ran Wang, Hua Zuo, Zhen Fang, Jie Lu
2025 J jnl
Learning Robust Spectral Dynamics for Temporal Domain Generalization.
CoRR
En Yu, Jie Lu, Xiaoyu Yang, Guangquan Zhang, Zhen Fang
2025 J jnl
MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction.
Briefings Bioinform.
Yue Yang, Kairui Guo, Yonggang Zhang, Zhen Fang, Hua Lin, Mark Grosser, Deon Venter, Weihai Lu, Mengjia Wu, Dennis Cordato, Guangquan Zhang, Jie Lu
2025 A* conf
MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection.
ACM Multimedia
Kuo Shi, Jie Lu, Shanshan Ye, Guangquan Zhang, Zhen Fang
2025 J jnl
MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection.
CoRR
Kuo Shi, Jie Lu, Shanshan Ye, Guangquan Zhang, Zhen Fang
2025 J jnl
Multiview Classification Through Learning From Interval-Valued Data.
IEEE Trans. Neural Networks Learn. Syst.
Guangzhi Ma, Jie Lu, Zhen Fang, Feng Liu, Guangquan Zhang
2025 A* conf
NLPrompt: Noise-Label Prompt Learning for Vision-Language Models.
CVPR
Bikang Pan, Qun Li, Xiaoying Tang, Wei Huang, Zhen Fang, Feng Liu, Jingya Wang, Jingyi Yu, Ye Shi
2025 J jnl
On the Provable Importance of Gradients for Language-Assisted Image Clustering.
CoRR
Bo Peng, Jie Lu, Guangquan Zhang, Zhen Fang
2025 J jnl
Out-of-Distribution Detection with Virtual Outlier Smoothing.
Int. J. Comput. Vis.
Jun Nie, Yadan Luo, Shanshan Ye, Yonggang Zhang, Xinmei Tian, Zhen Fang
2025 J jnl
Out-of-distribution detection with non-semantic exploration.
Inf. Sci.
Zhen Fang, Jie Lu, Guangquan Zhang
2025 J jnl
Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents.
CoRR
Zhizhen Zhang, Lei Zhu, Zhen Fang, Zi Huang, Yadan Luo
2025 A* conf
Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer.
ICLR
Ningyuan Zhang, Jie Lu, Keqiuyin Li, Zhen Fang, Guangquan Zhang
2025 J jnl
SENA: Leveraging set-level consistency adversarial learning for robust pre-trained language model adaptation.
Knowl. Based Syst.
Jianqi Gao, Jian Cao, Hang Yu, Yonggang Zhang, Zhen Fang
2025 J jnl
Shaking to Reveal: Perturbation-Based Detection of LLM Hallucinations.
CoRR
Jinyuan Luo, Zhen Fang, Yixuan Li, Seongheon Park, Ling Chen
2025 A* conf
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach.
ICML
Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li
2025 J jnl
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach.
CoRR
Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li
2024 J jnl
A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data.
CoRR
Feng Gu, Jie Lu, Zhen Fang, Kun Wang, Guangquan Zhang
2024 J jnl
An Extremely Simple Algorithm for Source Domain Reconstruction.
IEEE Trans. Cybern.
Zhen Fang, Jie Lu, Guangquan Zhang
2024 B conf
CLIP-Enhanced Unsupervised Domain Adaptation with Consistency Regularization.
IJCNN
Kuo Shi, Jie Lu, Zhen Fang, Guangquan Zhang
2024 A* conf
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection.
ICLR
Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang
2024 J jnl
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection.
CoRR
Bo Peng, Yadan Luo, Yonggang Zhang, Yixuan Li, Zhen Fang
2024 J jnl
Domain Adaptation With Interval-Valued Observations: Theory and Algorithms.
IEEE Trans. Fuzzy Syst.
Guangzhi Ma, Jie Lu, Feng Liu, Zhen Fang, Guangquan Zhang
2024 — conf
Enhancing Vision-Language Models Incorporating TSK Fuzzy System for Domain Adaptation.
FUZZ
Kuo Shi, Jie Lu, Zhen Fang, Guangquan Zhang
2024 J jnl
Exclusive Style Removal for Cross Domain Novel Class Discovery.
CoRR
Yicheng Wang, Feng Liu, Junmin Liu, Zhen Fang, Kai Sun
2024 A* conf
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
ICLR
Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
2024 J jnl
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
CoRR
Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
2024 A* conf
Knowledge Distillation with Auxiliary Variable.
ICML
Bo Peng, Zhen Fang, Guangquan Zhang, Jie Lu
2024 A* conf
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection.
NeurIPS
Yonggang Zhang, Jie Lu, Bo Peng, Zhen Fang, Yiu-ming Cheung
2024 J jnl
Multiclass Classification With Fuzzy-Feature Observations: Theory and Algorithms.
IEEE Trans. Cybern.
Guangzhi Ma, Jie Lu, Feng Liu, Zhen Fang, Guangquan Zhang
2024 J jnl
NLPrompt: Noise-Label Prompt Learning for Vision-Language Models.
CoRR
Bikang Pan, Qun Li, Xiaoying Tang, Wei Huang, Zhen Fang, Feng Liu, Jingya Wang, Jingyi Yu, Ye Shi
2024 A* conf
Negative Label Guided OOD Detection with Pretrained Vision-Language Models.
ICLR
Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2024 J jnl
Negative Label Guided OOD Detection with Pretrained Vision-Language Models.
CoRR
Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2024 A* conf
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation.
ICLR
Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han
2024 J jnl
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation.
CoRR
Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian, Bo Han
2024 J jnl
On the Learnability of Out-of-distribution Detection.
CoRR
Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu
2024 J jnl
On the Learnability of Out-of-distribution Detection.
J. Mach. Learn. Res.
Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu
2024 A* conf
Out-of-Distribution Detection with Negative Prompts.
ICLR
Jun Nie, Yonggang Zhang, Zhen Fang, Tongliang Liu, Bo Han, Xinmei Tian
2024 B conf
Prompt-Based Memory Bank for Continual Test-Time Domain Adaptation in Vision-Language Models.
IJCNN
Ran Wang, Hua Zuo, Zhen Fang, Jie Lu
2024 J jnl
Source-Free Unsupervised Domain Adaptation: Current research and future directions.
Neurocomputing
Ningyuan Zhang, Jie Lu, Keqiuyin Li, Zhen Fang, Guangquan Zhang
2024 A* conf
Spatio-temporal Heterogeneous Federated Learning for Time Series Classification with Multi-view Orthogonal Training.
ACM Multimedia
Chenrui Wu, Haishuai Wang, Xiang Zhang, Zhen Fang, Jiajun Bu
2024 A* conf
Towards Robustness Prompt Tuning with Fully Test-Time Adaptation for CLIP's Zero-Shot Generalization.
ACM Multimedia
Ran Wang, Hua Zuo, Zhen Fang, Jie Lu
2024 J jnl
Unsupervised Domain Adaptation Enhanced by Fuzzy Prompt Learning.
IEEE Trans. Fuzzy Syst.
Kuo Shi, Jie Lu, Zhen Fang, Guangquan Zhang
2024 J jnl
Where and How to Transfer: Knowledge Aggregation-Induced Transferability Perception for Unsupervised Domain Adaptation.
IEEE Trans. Pattern Anal. Mach. Intell.
Jiahua Dong, Yang Cong, Gan Sun, Zhen Fang, Zhengming Ding
2023 J jnl
Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation.
IEEE Trans. Neural Networks Learn. Syst.
Zhong Li, Zhen Fang, Feng Liu, Bo Yuan, Guangquan Zhang, Jie Lu
2023 A* conf
Continual Named Entity Recognition without Catastrophic Forgetting.
EMNLP
Duzhen Zhang, Wei Cong, Jiahua Dong, Yahan Yu, Xiuyi Chen, Yonggang Zhang, Zhen Fang
2023 J jnl
Continual Named Entity Recognition without Catastrophic Forgetting.
CoRR
Duzhen Zhang, Wei Cong, Jiahua Dong, Yahan Yu, Xiuyi Chen, Yonggang Zhang, Zhen Fang
2023 A* conf
Detecting Out-of-distribution Data through In-distribution Class Prior.
ICML
Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han
2023 A* conf
Invariant Learning via Probability of Sufficient and Necessary Causes.
NeurIPS
Mengyue Yang, Yonggang Zhang, Zhen Fang, Yali Du, Furui Liu, Jean-Francois Ton, Jianhong Wang, Jun Wang
2023 J jnl
Invariant Learning via Probability of Sufficient and Necessary Causes.
CoRR
Mengyue Yang, Zhen Fang, Yonggang Zhang, Yali Du, Furui Liu, Jean-Francois Ton, Jun Wang
2023 J jnl
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection.
CoRR
Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Zi Huang, Mahsa Baktashmotlagh
2023 A* conf
Kecor: Kernel Coding Rate Maximization for Active 3D Object Detection.
ICCV
Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Mahsa Baktashmotlagh, Zi Huang
2023 J jnl
Learning to Augment Distributions for Out-of-Distribution Detection.
CoRR
Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
2023 A* conf
Learning to Augment Distributions for Out-of-distribution Detection.
NeurIPS
Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
2023 A* conf
Meta OOD Learning For Continuously Adaptive OOD Detection.
ICCV
Xinheng Wu, Jie Lu, Zhen Fang, Guangquan Zhang
2023 J jnl
Meta OOD Learning for Continuously Adaptive OOD Detection.
CoRR
Xinheng Wu, Jie Lu, Zhen Fang, Guangquan Zhang
2023 A* conf
Moderately Distributional Exploration for Domain Generalization.
ICML
Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han, Xinmei Tian
2023 J jnl
Moderately Distributional Exploration for Domain Generalization.
CoRR
Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han, Xinmei Tian
2023 C conf
Multi-model Transfer Learning and Genotypic Analysis for Seizure Type Classification.
HIS
Yue Yang, Kairui Guo, Zhen Fang, Hua Lin, Mark Grosser, Jie Lu
2023 — conf
Multiple Teacher Model for Continual Test-Time Domain Adaptation.
AI (1)
Ran Wang, Hua Zuo, Zhen Fang, Jie Lu
2023 B conf
One-step Domain Adaptation Approach with Partial Label.
IJCNN
Guohang Zeng, Zhen Fang, Guangquan Zhang, Jie Lu
2023 A* conf
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources.
NeurIPS
Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
2023 J jnl
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources.
CoRR
Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
2023 A* conf
SODA: Robust Training of Test-Time Data Adaptors.
NeurIPS
Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han
2023 J jnl
SODA: Robust Training of Test-Time Data Adaptors.
CoRR
Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang, Bo Han
2023 J jnl
Semi-Supervised Heterogeneous Domain Adaptation: Theory and Algorithms.
IEEE Trans. Pattern Anal. Mach. Intell.
Zhen Fang, Jie Lu, Feng Liu, Guangquan Zhang
2022 A* conf
Federated Class-Incremental Learning.
CVPR
Jiahua Dong, Lixu Wang, Zhen Fang, Gan Sun, Shichao Xu, Xiao Wang, Qi Zhu
2022 J jnl
Federated Class-Incremental Learning.
CoRR
Jiahua Dong, Lixu Wang, Zhen Fang, Gan Sun, Shichao Xu, Xiao Wang, Qi Zhu
2022 A* conf
Is Out-of-Distribution Detection Learnable?
NeurIPS
Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu
2022 J jnl
Is Out-of-Distribution Detection Learnable?
CoRR
Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu
2022 J jnl
Learning From a Complementary-Label Source Domain: Theory and Algorithms.
IEEE Trans. Neural Networks Learn. Syst.
Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu
2022 J jnl
Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms.
CoRR
Guangzhi Ma, Jie Lu, Feng Liu, Zhen Fang, Guangquan Zhang
2021 — —
Bridging Theory and Algorithms for Open-Set and Heterogeneous Domain Adaptations
Zhen Fang
2021 A* conf
Confident Anchor-Induced Multi-Source Free Domain Adaptation.
NeurIPS
Jiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu
2021 A* conf
How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
AAAI
Zhong Li, Zhen Fang, Feng Liu, Jie Lu, Bo Yuan, Guangquan Zhang
2021 J jnl
How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
CoRR
Zhong Li, Zhen Fang, Feng Liu, Jie Lu, Bo Yuan, Guangquan Zhang
2021 A* conf
Learning Bounds for Open-Set Learning.
ICML
Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang
2021 J jnl
Learning Bounds for Open-Set Learning.
CoRR
Zhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang
2021 J jnl
Open Set Domain Adaptation: Theoretical Bound and Algorithm.
IEEE Trans. Neural Networks Learn. Syst.
Zhen Fang, Jie Lu, Feng Liu, Junyu Xuan, Guangquan Zhang
2020 J jnl
Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation.
CoRR
Zhong Li, Zhen Fang, Feng Liu, Bo Yuan, Guangquan Zhang, Jie Lu
2020 A* conf
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation.
IJCAI
Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu
2020 J jnl
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation.
CoRR
Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu
2020 J jnl
Learning from a Complementary-label Source Domain: Theory and Algorithms.
CoRR
Yiyang Zhang, Feng Liu, Zhen Fang, Bo Yuan, Guangquan Zhang, Jie Lu
2019 J jnl
Open Set Domain Adaptation: Theoretical Bound and Algorithm.
CoRR
Zhen Fang, Jie Lu, Feng Liu, Junyu Xuan, Guangquan Zhang
2019 B conf
Unsupervised Domain Adaptation with Sphere Retracting Transformation.
IJCNN
Zhen Fang, Jie Lu, Feng Liu, Guangquan Zhang