Yongyi Su - RankMe

35 papers A* 8C 1Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization. AAAI Jingyi Liao, Yongyi Su, Rong-Cheng Tu, Zhao Jin, Wenhao Sun, Yiting Li, Xun Xu, Dacheng Tao, XuLei Yang
2026	A*	`conf`	Enhancing Generalization of Depth Estimation Foundation Model via Weakly-Supervised Adaptation with Regularization. AAAI Yan Huang, Yongyi Su, Xin Lin, Le Zhang, Xun Xu
2025	J	`jnl`	AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization. CoRR Jingyi Liao, Yongyi Su, Rong-Cheng Tu, Zhao Jin, Wenhao Sun, Yiting Li, Dacheng Tao, Xun Xu, XuLei Yang
2025	—	`conf`	Augmented Contrastive Clustering with Uncertainty-Aware Prototyping for Time Series Test Time Adaptation. KDD (1) Peiliang Gong, Mohamed Ragab, Min Wu, Zhenghua Chen, Yongyi Su, Xiaoli Li, Daoqiang Zhang
2025	J	`jnl`	Augmented Contrastive Clustering with Uncertainty-Aware Prototyping for Time Series Test Time Adaptation. CoRR Peiliang Gong, Mohamed Ragab, Min Wu, Zhenghua Chen, Yongyi Su, Xiaoli Li, Daoqiang Zhang
2025	J	`jnl`	Bidirectional Segmentation-Aware Network for One-Shot Object Detection. Neurocomputing Wenwen Zhang, Zhenghua Chen, Yongyi Su, Zhiyu Xiang, Hangguan Shan, Eryun Liu
2025	A*	`conf`	Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model. ICLR Yushu Li, Yongyi Su, Adam Goodge, Kui Jia, Xun Xu
2025	J	`jnl`	Enhancing Generalization of Depth Estimation Foundation Model via Weakly-Supervised Adaptation with Regularization. CoRR Yan Huang, Yongyi Su, Xin Lin, Le Zhang, Xun Xu
2025	J	`jnl`	Mitigating Missing Feature Channels at Inference Stage: Test-Time Adaptation Through Self-Training With Data Imputation. IEEE Signal Process. Lett. Yan Huang, Yongyi Su, XuLei Yang, Xin Lin, Xun Xu
2025	A*	`conf`	On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning. ICLR Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, XuLei Yang, Chuan-Sheng Foo, Xun Xu
2025	J	`jnl`	Patch-as-Decodable-Token: Towards Unified Multi-Modal Vision Tasks in MLLMs. CoRR 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
2025	J	`jnl`	PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. Nanqing Liu, Xun Xu, Yongyi Su, Haojie Zhang, Heng-Chao Li
2025	J	`jnl`	Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift. CoRR Jingyi Liao, Xun Xu, Yongyi Su, Rong-Cheng Tu, Yifan Liu, Dacheng Tao, XuLei Yang
2025	—	`conf`	SODA: Out-of-Distribution Detection in Domain-Shifted Point Clouds via Neighborhood Propagation. ECML/PKDD (1) Adam Goodge, Bryan Hooi, Jingyi Liao, Yongyi Su, Wee Siong Ng, Xun Xu, XuLei Yang
2025	J	`jnl`	SODA: Out-of-Distribution Detection in Domain-Shifted Point Clouds via Neighborhood Propagation. CoRR Adam Goodge, Xun Xu, Bryan Hooi, Wee Siong Ng, Jingyi Liao, Yongyi Su, XuLei Yang
2024	J	`jnl`	CLIP-guided Source-free Object Detection in Aerial Images. CoRR Nanqing Liu, Xun Xu, Yongyi Su, Chengxin Liu, Peiliang Gong, Heng-Chao Li
2024	C	`conf`	Clip-Guided Source-Free Object Detection in Aerial Images. IGARSS Nanqing Liu, Xun Xu, Yongyi Su, Chengxin Liu, Peiliang Gong, Heng-Chao Li
2024	J	`jnl`	Efficient and Context-Aware Label Propagation for Zero-/Few-Shot Training-Free Adaptation of Vision-Language Model. CoRR Yushu Li, Yongyi Su, Adam Goodge, Kui Jia, Xun Xu
2024	J	`jnl`	Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection. CoRR Yushu Li, Yongyi Su, XuLei Yang, Kui Jia, Xun Xu
2024	J	`jnl`	Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection. Trans. Mach. Learn. Res. Yushu Li, Yongyi Su, XuLei Yang, Kui Jia, Xun Xu
2024	A*	`conf`	Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation. CVPR Haojie Zhang, Yongyi Su, Xun Xu, Kui Jia
2024	J	`jnl`	On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning. CoRR Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, XuLei Yang, Chuan-Sheng Foo, Xun Xu
2024	J	`jnl`	PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images. CoRR Nanqing Liu, Xun Xu, Yongyi Su, Haojie Zhang, Heng-Chao Li
2024	J	`jnl`	Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training. IEEE Trans. Pattern Anal. Mach. Intell. Yongyi Su, Xun Xu, Tianrui Li, Kui Jia
2024	A*	`conf`	Towards Real-World Test-Time Adaptation: Tri-net Self-Training with Balanced Normalization. AAAI Yongyi Su, Xun Xu, Kui Jia
2023	J	`jnl`	Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation. CoRR Haojie Zhang, Yongyi Su, Xun Xu, Kui Jia
2023	A*	`conf`	On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion. ICCV Yushu Li, Xun Xu, Yongyi Su, Kui Jia
2023	J	`jnl`	On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion. CoRR Yushu Li, Xun Xu, Yongyi Su, Kui Jia
2023	J	`jnl`	Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training. CoRR Yongyi Su, Xun Xu, Tianrui Li, Kui Jia
2023	J	`jnl`	STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization. CoRR Yijin Chen, Xun Xu, Yongyi Su, Kui Jia
2023	J	`jnl`	Towards Real-World Test-Time Adaptation: Tri-Net Self-Training with Balanced Normalization. CoRR Yongyi Su, Xun Xu, Kui Jia
2023	J	`jnl`	Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning. IEEE Trans. Circuits Syst. Video Technol. Yongyi Su, Xun Xu, Kui Jia
2022	A*	`conf`	Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering. NeurIPS Yongyi Su, Xun Xu, Kui Jia
2022	J	`jnl`	Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering. CoRR Yongyi Su, Xun Xu, Kui Jia
2022	J	`jnl`	Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning. CoRR Yongyi Su, Xun Xu, Kui Jia