| 2026 | AAAI | Enhancing Generalization of Depth Estimation Foundation Model via Weakly-Supervised Adaptation with Regularization. | Yan Huang, Yongyi Su, Xin Lin, Le Zhang, Xun Xu |
| 2026 | AAAI | AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization. | Jingyi Liao, Yongyi Su, Rong-Cheng Tu, Zhao Jin, Wenhao Sun, Yiting Li, Xun Xu, Dacheng Tao, Xulei Yang |
| 2025 | ICLR | Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model. | Yushu Li, Yongyi Su, Adam Goodge, Kui Jia, Xun Xu |
| 2025 | ICLR | On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning. | Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, Xulei Yang, Chuan-Sheng Foo, Xun Xu |
| 2025 | KDD | Augmented Contrastive Clustering with Uncertainty-Aware Prototyping for Time Series Test Time Adaptation. | Peiliang Gong, Mohamed Ragab, Min Wu, Zhenghua Chen, Yongyi Su, Xiaoli Li, Daoqiang Zhang |
| 2024 | AAAI | Towards Real-World Test-Time Adaptation: Tri-net Self-Training with Balanced Normalization. | Yongyi Su, Xun Xu, Kui Jia |
| 2024 | CVPR | Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation. | Haojie Zhang, Yongyi Su, Xun Xu, Kui Jia |
| 2024 | IGARSS | Clip-Guided Source-Free Object Detection in Aerial Images. | Nanqing Liu, Xun Xu, Yongyi Su, Chengxin Liu, Peiliang Gong, Heng-Chao Li |
| 2023 | ICCV | On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion. | Yushu Li, Xun Xu, Yongyi Su, Kui Jia |