Yongyi Su

According to our database, Yongyi Su authored at least 20 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

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

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Enhancing Generalization of Depth Estimation Foundation Model via Weakly-Supervised Adaptation with Regularization.

Yan Huang, Yongyi Su, Xin Lin, Le Zhang, Xun Xu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Patch-as-Decodable-Token: Towards Unified Multi-Modal Vision Tasks in MLLMs.

Yongyi Su, Haojie Zhang, Shijie Li, Nanqing Liu, Jingyi Liao, Junyi Pan, Yuan Liu, Xiaofen Xing, Chong Sun, Chen Li, Nancy F. Chen, Shuicheng Yan, Xulei Yang, Xun Xu

CoRR, October, 2025

Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift.

Jingyi Liao, Xun Xu, Yongyi Su, Rong-Cheng Tu, Yifan Liu, Dacheng Tao, Xulei Yang

CoRR, March, 2025

PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images.

Nanqing Liu, Xun Xu, Yongyi Su, Haojie Zhang, Heng-Chao Li

IEEE Trans. Geosci. Remote. Sens., 2025

Mitigating Missing Feature Channels at Inference Stage: Test-Time Adaptation Through Self-Training With Data Imputation.

Yan Huang, Yongyi Su, Xulei Yang, Xin Lin, Xun Xu

IEEE Signal Process. Lett., 2025

Bidirectional Segmentation-Aware Network for One-Shot Object Detection.

Wenwen Zhang, Zhenghua Chen, Yongyi Su, Zhiyu Xiang, Hangguan Shan, Eryun Liu

Neurocomputing, 2025

SODA: Out-of-Distribution Detection in Domain-Shifted Point Clouds via Neighborhood Propagation.

Adam Goodge, Bryan Hooi, Jingyi Liao, Yongyi Su, Wee Siong Ng, Xun Xu, Xulei Yang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

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

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training.

Yongyi Su, Xun Xu, Tianrui Li, Kui Jia

IEEE Trans. Pattern Anal. Mach. Intell., August, 2024

Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection.

Yushu Li, Yongyi Su, Xulei Yang, Kui Jia, Xun Xu

Trans. Mach. Learn. Res., 2024

Clip-Guided Source-Free Object Detection in Aerial Images.

Nanqing Liu, Xun Xu, Yongyi Su, Chengxin Liu, Peiliang Gong, Heng-Chao Li

Proceedings of the IGARSS 2024, 2024

Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation.

Haojie Zhang, Yongyi Su, Xun Xu, Kui Jia

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Towards Real-World Test-Time Adaptation: Tri-net Self-Training with Balanced Normalization.

Yongyi Su, Xun Xu, Kui Jia

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning.

Yongyi Su, Xun Xu, Kui Jia

IEEE Trans. Circuits Syst. Video Technol., December, 2023

STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization.

Yijin Chen, Xun Xu, Yongyi Su, Kui Jia

CoRR, 2023

On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion.

Yushu Li, Xun Xu, Yongyi Su, Kui Jia

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering.

Yongyi Su, Xun Xu, Kui Jia

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022