| Safe deep semi-supervised learning for unseen-class unlabeled data LZ Guo, ZY Zhang, Y Jiang, YF Li, ZH Zhou International conference on machine learning, 3897-3906, 2020 | 294 | 2020 |
| Towards safe weakly supervised learning YF Li, LZ Guo, ZH Zhou IEEE transactions on pattern analysis and machine intelligence 43 (1), 334-346, 2019 | 203 | 2019 |
| Usb: A unified semi-supervised learning benchmark for classification Y Wang, H Chen, Y Fan, W Sun, R Tao, W Hou, R Wang, L Yang, Z Zhou, ... Advances in Neural Information Processing Systems 35, 3938-3961, 2022 | 197 | 2022 |
| Class-imbalanced semi-supervised learning with adaptive thresholding LZ Guo, YF Li International conference on machine learning, 8082-8094, 2022 | 165 | 2022 |
| Lawgpt: A chinese legal knowledge-enhanced large language model Z Zhou, JX Shi, PX Song, XW Yang, YX Jin, LZ Guo, YF Li arXiv preprint arXiv:2406.04614, 2024 | 73 | 2024 |
| Robust semi-supervised learning when not all classes have labels LZ Guo, YG Zhang, ZF Wu, JJ Shao, YF Li Advances in neural information processing systems 35, 3305-3317, 2022 | 61 | 2022 |
| Interactive graph construction for graph-based semi-supervised learning C Chen, Z Wang, J Wu, X Wang, LZ Guo, YF Li, S Liu IEEE transactions on visualization and computer graphics 27 (9), 3701-3716, 2021 | 52 | 2021 |
| Ods: Test-time adaptation in the presence of open-world data shift Z Zhou, LZ Guo, LH Jia, D Zhang, YF Li International Conference on Machine Learning, 42574-42588, 2023 | 50 | 2023 |
| Step: Out-of-distribution detection in the presence of limited in-distribution labeled data Z Zhou, LZ Guo, Z Cheng, YF Li, S Pu Advances in Neural Information Processing Systems 34, 29168-29180, 2021 | 44 | 2021 |
| Learning safe multi-label prediction for weakly labeled data T Wei, LZ Guo, YF Li, W Gao Machine Learning 107 (4), 703-725, 2018 | 41 | 2018 |
| Learning from group supervision: the impact of supervision deficiency on multi-label learning M Xu, LZ Guo Science China Information Sciences 64 (3), 130101, 2021 | 29 | 2021 |
| Record: Resource constrained semi-supervised learning under distribution shift LZ Guo, Z Zhou, YF Li Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 23 | 2020 |
| Investigating the limitation of clip models: The worst-performing categories JJ Shao, JX Shi, XW Yang, LZ Guo, YF Li arXiv preprint arXiv:2310.03324, 2023 | 22 | 2023 |
| Identifying Useful Learnwares for Heterogeneous Label Spaces LZ Guo, Z Zhou, YF Li, ZH Zhou | 22 | 2023 |
| Step back to leap forward: Self-backtracking for boosting reasoning of language models XW Yang, XY Zhu, WD Wei, DC Zhang, JJ Shao, Z Zhou, LZ Guo, YF Li arXiv preprint arXiv:2502.04404, 2025 | 19 | 2025 |
| Transfer and share: semi-supervised learning from long-tailed data T Wei, QY Liu, JX Shi, WW Tu, LZ Guo Machine Learning 113 (4), 1725-1742, 2024 | 19 | 2024 |
| A general formulation for safely exploiting weakly supervised data LZ Guo, YF Li Proceedings of the AAAI conference on Artificial Intelligence 32 (1), 2018 | 19 | 2018 |
| Open-set learning under covariate shift JJ Shao, XW Yang, LZ Guo Machine Learning 113 (4), 1643-1659, 2024 | 15 | 2024 |
| Interactive reweighting for mitigating label quality issues W Yang, Y Guo, J Wu, Z Wang, LZ Guo, YF Li, S Liu IEEE Transactions on Visualization and Computer Graphics 30 (3), 1837-1852, 2023 | 15 | 2023 |
| Bridging internal probability and self-consistency for effective and efficient llm reasoning Z Zhou, T Yuhao, Z Li, Y Yao, LZ Guo, X Ma, YF Li arXiv preprint arXiv:2502.00511, 2025 | 14 | 2025 |
Yu-Feng LiProfessor, Nanjing UniversityVerified email at lamda.nju.edu.cn
