| 2025 | ICLR | Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model. | Rundong He, Yicong Dong, Lanzhe Guo, Yilong Yin, Tailin Wu |
| 2024 | AAAI | Exploring Channel-Aware Typical Features for Out-of-Distribution Detection. | Rundong He, Yue Yuan, Zhongyi Han, Fan Wang, Wan Su, Yilong Yin, Tongliang Liu, Yongshun Gong |
| 2024 | CVPR | Discriminability-Driven Channel Selection for Out-of-Distribution Detection. | Yue Yuan, Rundong He, Yicong Dong, Zhongyi Han, Yilong Yin |
| 2023 | AAAI | Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation. | Zhongyi Han, Zhiyan Zhang, Fan Wang, Rundong He, Wan Su, Xiaoming Xi, Yilong Yin |
| 2023 | CVPR | MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation. | Fan Wang, Zhongyi Han, Zhiyan Zhang, Rundong He, Yilong Yin |
| 2022 | AAAI | Not All Parameters Should Be Treated Equally: Deep Safe Semi-supervised Learning under Class Distribution Mismatch. | Rundong He, Zhongyi Han, Yang Yang, Yilong Yin |
| 2022 | ACML | SNAIL: Semi-Separated Uncertainty Adversarial Learning for Universal Domain Adaptation. | Zhongyi Han, Wan Su, Rundong He, Yilong Yin |
| 2022 | CVPR | Safe-Student for Safe Deep Semi-Supervised Learning with Unseen-Class Unlabeled Data. | Rundong He, Zhongyi Han, Xiankai Lu, Yilong Yin |