Publications

2026

1. ICML

   

   Discretized Density-Guided Source-Free Domain Adaptation for Regression

   Gezheng Xu, Qi Chen, Qiuhao Zeng, Charles Ling, and Boyu Wang

   In International Conference on Machine Learning (ICML), 2026

   Bib

   @inproceedings{xu2026discretized,
     author = {Xu, Gezheng and Chen, Qi and Zeng, Qiuhao and Ling, Charles and Wang, Boyu},
     title = {Discretized Density-Guided Source-Free Domain Adaptation for Regression},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2026},
   }

2. ICML

   FUSE: Full-spectrum Unlearnable Examples via Spectral Equalization

   Jiale Cai, Gezheng Xu, Zhihao Li, Ruiyi Fang, Ruizhi Pu, Di Wu, Qicheng Lao, Charles Ling, and Boyu Wang

   In International Conference on Machine Learning (ICML), 2026

   Bib

   @inproceedings{cai2026fuse,
     author = {Cai, Jiale and Xu, Gezheng and Li, Zhihao and Fang, Ruiyi and Pu, Ruizhi and Wu, Di and Lao, Qicheng and Ling, Charles and Wang, Boyu},
     title = {{FUSE}: Full-spectrum Unlearnable Examples via Spectral Equalization},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2026},
   }

3. ICML

   Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates

   Linxiao Yang, Xue Jiang, Gezheng Xu, Tian Zhou, Min Yang, ZhaoYang Zhu, Linyuan Geng, Zhipeng Zeng, Qiming Chen, Xinyue Gu, Rong Jin, and Liang Sun

   In International Conference on Machine Learning (ICML), 2026

   Bib

   @inproceedings{yang2026baguan,
     author = {Yang, Linxiao and Jiang, Xue and Xu, Gezheng and Zhou, Tian and Yang, Min and Zhu, ZhaoYang and Geng, Linyuan and Zeng, Zhipeng and Chen, Qiming and Gu, Xinyue and Jin, Rong and Sun, Liang},
     title = {Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2026},
   }

4. ICML

   Attention with Routed-Memory for Learnable Sparse Control

   Qiuhao Zeng, Jerry Huang, Peng Lu, Ruiyi Fang, Gezheng Xu, Zihao Jing, Yufei Cui, Charles Ling, Gang Niu, and Boyu Wang

   In International Conference on Machine Learning (ICML), 2026

   Bib

   @inproceedings{zeng2026attention,
     author = {Zeng, Qiuhao and Huang, Jerry and Lu, Peng and Fang, Ruiyi and Xu, Gezheng and Jing, Zihao and Cui, Yufei and Ling, Charles and Niu, Gang and Wang, Boyu},
     title = {Attention with Routed-Memory for Learnable Sparse Control},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2026},
   }

5. ICLR

   When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining

   Zhihao Li, Gezheng Xu, Jiale Cai, Ruiyi Fang, Di Wu, Qicheng Lao, Charles Ling, and Boyu Wang

   In International Conference on Learning Representations (ICLR), 2026

   Bib

   @inproceedings{li2026priors,
     author = {Li, Zhihao and Xu, Gezheng and Cai, Jiale and Fang, Ruiyi and Wu, Di and Lao, Qicheng and Ling, Charles and Wang, Boyu},
     title = {When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining},
     booktitle = {International Conference on Learning Representations (ICLR)},
     year = {2026},
   }

2025

1. TPAMI

   

   Unraveling the Mysteries of Label Noise in Source-Free Domain Adaptation: Theory and Practice

   Gezheng Xu^*, Li Yi^*, Pengcheng Xu, Jiaqi Li, Ruizhi Pu, Changjian Shui, Charles Ling, A. Ian McLeod, and Boyu Wang

   IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

   DOI Bib Code

   @article{xu2025unraveling,
     author = {Xu, Gezheng and Yi, Li and Xu, Pengcheng and Li, Jiaqi and Pu, Ruizhi and Shui, Changjian and Ling, Charles and McLeod, A. Ian and Wang, Boyu},
     journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
     title = {Unraveling the Mysteries of Label Noise in Source-Free Domain Adaptation: Theory and Practice},
     year = {2025},
     doi = {10.1109/TPAMI.2025.3536845},
   }

2. ICLR

   

   Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control

   Gezheng Xu^*, Hui Guo^*, Li Yi, Charles Ling, Boyu Wang, and Grace Yi

   In International Conference on Learning Representations (ICLR), 2025

   Bib Code

   @inproceedings{xu2025revisiting,
     title = {Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control},
     author = {Xu, Gezheng and Guo, Hui and Yi, Li and Ling, Charles and Wang, Boyu and Yi, Grace},
     booktitle = {International Conference on Learning Representations (ICLR)},
     year = {2025},
   }

3. NeurIPS

   Versatile Transferable Unlearnable Example Generator

   Zhihao Li, Jiale Cai, Gezheng Xu, Hao Zheng, Qiuyue Li, Fan Zhou, Shichun Yang, Charles Ling, and Boyu Wang

   In Neural Information Processing Systems (NeurIPS), 2025

   Bib

   @inproceedings{li2025versatile,
     author = {Li, Zhihao and Cai, Jiale and Xu, Gezheng and Zheng, Hao and Li, Qiuyue and Zhou, Fan and Yang, Shichun and Ling, Charles and Wang, Boyu},
     title = {Versatile Transferable Unlearnable Example Generator},
     booktitle = {Neural Information Processing Systems (NeurIPS)},
     year = {2025},
   }

4. ICML

   Homophily Enhanced Graph Domain Adaptation

   Ruiyi Fang, Bingheng Li, Jingyu Zhao, Ruizhi Pu, Qiuhao Zeng, Gezheng Xu, Charles Ling, and Boyu Wang

   In International Conference on Machine Learning (ICML), 2025

   Bib

   @inproceedings{fang2025homophily,
     author = {Fang, Ruiyi and Li, Bingheng and Zhao, Jingyu and Pu, Ruizhi and Zeng, Qiuhao and Xu, Gezheng and Ling, Charles and Wang, Boyu},
     title = {Homophily Enhanced Graph Domain Adaptation},
     booktitle = {International Conference on Machine Learning (ICML)},
     year = {2025},
   }

5. TMLR

   Uniform Noise Distribution and Compact Clusters: Unveil the Key to Self-Supervised Learning’s Success in Label Noise

   Pengcheng Xu, Li Yi, Gezheng Xu, Xi Chen, Ian McLeod, Charles Ling, and Boyu Wang

   Transactions on Machine Learning Research, 2025

   Bib

   @article{xu2025uniform,
     author = {Xu, Pengcheng and Yi, Li and Xu, Gezheng and Chen, Xi and McLeod, Ian and Ling, Charles and Wang, Boyu},
     title = {Uniform Noise Distribution and Compact Clusters: Unveil the Key to Self-Supervised Learning's Success in Label Noise},
     journal = {Transactions on Machine Learning Research},
     year = {2025},
   }

6. Neural Networks

   FedELR: When Federated Learning Meets Learning With Noisy Labels

   Ruizhi Pu, Lixing Yu, Shaojie Zhan, Gezheng Xu, Fan Zhou, Charles Ling, and Boyu Wang

   Neural Networks, 2025

   Bib

   @article{pu2025fedelr,
     author = {Pu, Ruizhi and Yu, Lixing and Zhan, Shaojie and Xu, Gezheng and Zhou, Fan and Ling, Charles and Wang, Boyu},
     title = {{FedELR}: When Federated Learning Meets Learning With Noisy Labels},
     journal = {Neural Networks},
     volume = {187},
     pages = {107275},
     year = {2025},
   }

7. ICLR

   

   ZETA: Leveraging Z-order Curves for Efficient Top-k Attention

   Qiuhao Zeng, Jerry Huang, Peng Lu, Gezheng Xu, Boxing Chen, Charles Ling, and Boyu Wang

   International Conference on Learning Representations (ICLR), 2025

   Bib

   @article{zeng2025zeta,
     author = {Zeng, Qiuhao and Huang, Jerry and Lu, Peng and Xu, Gezheng and Chen, Boxing and Ling, Charles and Wang, Boyu},
     title = {ZETA: Leveraging Z-order Curves for Efficient Top-k Attention},
     journal = {International Conference on Learning Representations (ICLR)},
     year = {2025},
   }

8. AAAI

   

   Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression

   Ruizhi Pu, Gezheng Xu, Ruiyi Fang, Binkun Bao, Charles X Ling, and Boyu Wang

   AAAI Conference on Artificial Intelligence (AAAI), 2025

   Bib

   @article{pu2024leveraging,
     author = {Pu, Ruizhi and Xu, Gezheng and Fang, Ruiyi and Bao, Binkun and Ling, Charles X and Wang, Boyu},
     title = {Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression},
     journal = {AAAI Conference on Artificial Intelligence (AAAI)},
     year = {2025},
   }

2024

1. ICML

   

   Intersectional Unfairness Discovery

   Gezheng Xu, Qi Chen, Charles Ling, Boyu Wang, and Changjian Shui

   In International Conference on Machine Learning (ICML), 2024

   Bib HTML PDF Code Poster

   @inproceedings{pmlr-v235-xu24d,
     title = {Intersectional Unfairness Discovery},
     author = {Xu, Gezheng and Chen, Qi and Ling, Charles and Wang, Boyu and Shui, Changjian},
     booktitle = {International Conference on Machine Learning (ICML)},
     pages = {54888--54917},
     year = {2024},
     editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix},
     volume = {235},
     series = {Proceedings of Machine Learning Research},
     publisher = {PMLR},
   }

2. AAAI

   

   Generalizing across Temporal Domains with Koopman Operators

   Qiuhao Zeng, Wei Wang, Fan Zhou, Gezheng Xu, Ruizhi Pu, Changjian Shui, Christian Gagné, Shichun Yang, Charles X. Ling, and Boyu Wang

   In AAAI Conference on Artificial Intelligence (AAAI), 2024

   Bib HTML

   @inproceedings{DBLP:conf/aaai/Zeng00XPS0YLW24,
     author = {Zeng, Qiuhao and Wang, Wei and Zhou, Fan and Xu, Gezheng and Pu, Ruizhi and Shui, Changjian and Gagn{\'{e}}, Christian and Yang, Shichun and Ling, Charles X. and Wang, Boyu},
     title = {Generalizing across Temporal Domains with Koopman Operators},
     booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
     pages = {16651--16659},
     year = {2024},
   }

2023

1. ICLR

   

   When Source-Free Domain Adaptation Meets Learning with Noisy Labels

   Li Yi^*, Gezheng Xu^*, Pengcheng Xu, Jiaqi Li, Ruizhi Pu, Charles Ling, A Ian McLeod, and Boyu Wang

   International Conference on Learning Representations (ICLR), 2023

   Bib Video Code Slides

   @article{yi2023source,
     title = {When Source-Free Domain Adaptation Meets Learning with Noisy Labels},
     author = {Yi, Li and Xu, Gezheng and Xu, Pengcheng and Li, Jiaqi and Pu, Ruizhi and Ling, Charles and McLeod, A Ian and Wang, Boyu},
     journal = {International Conference on Learning Representations (ICLR)},
     year = {2023},
   }

2. KBS

   

   Label Shift Conditioned Hybrid Querying for Deep Active Learning

   Jiaqi Li, Haojia Kong, Gezheng Xu, Changjian Shui, Ruizhi Pu, Zhao Kang, Charles X Ling, and Boyu Wang

   Knowledge-Based Systems, 2023

   Bib

   @article{li2023label,
     title = {Label Shift Conditioned Hybrid Querying for Deep Active Learning},
     author = {Li, Jiaqi and Kong, Haojia and Xu, Gezheng and Shui, Changjian and Pu, Ruizhi and Kang, Zhao and Ling, Charles X and Wang, Boyu},
     journal = {Knowledge-Based Systems},
     volume = {274},
     pages = {110616},
     year = {2023},
     publisher = {Elsevier},
   }

3. TKDE

   

   Towards more General Loss and Setting in Unsupervised Domain Adaptation

   Changjian Shui^*, Ruizhi Pu^*, Gezheng Xu, Jun Wen, Fan Zhou, Christian Gagné, Charles X Ling, and Boyu Wang

   IEEE Transactions on Knowledge and Data Engineering, 2023

   Bib

   @article{shui2023towards,
     title = {Towards more General Loss and Setting in Unsupervised Domain Adaptation},
     author = {Shui, Changjian and Pu, Ruizhi and Xu, Gezheng and Wen, Jun and Zhou, Fan and Gagn{\'e}, Christian and Ling, Charles X and Wang, Boyu},
     journal = {IEEE Transactions on Knowledge and Data Engineering},
     volume = {35},
     number = {10},
     pages = {10140--10150},
     year = {2023},
     publisher = {IEEE},
   }

4. JMLR

   

   Gap Minimization for Knowledge Sharing and Transfer

   Boyu Wang, Jorge A Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, and Eric Eaton

   Journal of Machine Learning Research, 2023

   Bib

   @article{wang2023gap,
     title = {Gap Minimization for Knowledge Sharing and Transfer},
     author = {Wang, Boyu and Mendez, Jorge A and Shui, Changjian and Zhou, Fan and Wu, Di and Xu, Gezheng and Gagn{\'e}, Christian and Eaton, Eric},
     journal = {Journal of Machine Learning Research},
     volume = {24},
     number = {33},
     pages = {1--57},
     year = {2023},
   }

2022

1. NeurIPS

   

   On Learning Fairness and Accuracy on Multiple Subgroups

   Changjian Shui^*, Gezheng Xu^*, Qi Chen, Jiaqi Li, Charles X Ling, Tal Arbel, Boyu Wang, and Christian Gagné

   Advances in Neural Information Processing Systems (NeurIPS), 2022

   Bib HTML Code

   @article{shui2022learning,
     title = {On Learning Fairness and Accuracy on Multiple Subgroups},
     author = {Shui, Changjian and Xu, Gezheng and Chen, Qi and Li, Jiaqi and Ling, Charles X and Arbel, Tal and Wang, Boyu and Gagn{\'e}, Christian},
     journal = {Advances in Neural Information Processing Systems (NeurIPS)},
     volume = {35},
     pages = {34121--34135},
     year = {2022},
   }

2021

1. BMC Bioinformatics

   

   External Features Enriched Model for Biomedical Question Answering

   Gezheng Xu, Wenge Rong, Yanmeng Wang, Yuanxin Ouyang, and Zhang Xiong

   BMC Bioinformatics, 2021

   Bib Code

   @article{xu2021external,
     title = {External Features Enriched Model for Biomedical Question Answering},
     author = {Xu, Gezheng and Rong, Wenge and Wang, Yanmeng and Ouyang, Yuanxin and Xiong, Zhang},
     journal = {BMC Bioinformatics},
     volume = {22},
     number = {1},
     pages = {272},
     year = {2021},
     publisher = {Springer},
   }