Tianxiang Zhao

57 papers A* 5A 11B 1Misc 1Journal 33Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models. CoRR Weijieying Ren, Jingxi Zhu, Zehao Liu, Tianxiang Zhao, Vasant G. Honavar
2025	Misc	`conf`	Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. ICASSP Xinlong Li, Weijieying Ren, Wei Qin, Lei Wang, Tianxiang Zhao, Richang Hong
2025	A	`conf`	Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs. WSDM Yilong Wang, Tianxiang Zhao, Zongyu Wu, Suhang Wang
2025	J	`jnl`	Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs. CoRR Yilong Wang, Tianxiang Zhao, Zongyu Wu, Suhang Wang
2025	J	`jnl`	Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions. CoRR Weijieying Ren, Tianxiang Zhao, Yuqing Huang, Vasant G. Honavar
2025	J	`jnl`	DiaLLMs: EHR Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. CoRR Weijieying Ren, Tianxiang Zhao, Lei Wang, Tianchun Wang, Vasant G. Honavar
2025	—	`conf`	DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. ACL (Findings) Weijieying Ren, Tianxiang Zhao, Lei Wang, Tianchun Wang, Vasant G. Honavar
2025	J	`jnl`	Enhance GNNs with Reliable Confidence Estimation via Adversarial Calibration Learning. CoRR Yilong Wang, Jiahao Zhang, Tianxiang Zhao, Suhang Wang
2025	J	`jnl`	Generalizing Test-time Compute-optimal Scaling as an Optimizable Graph. CoRR Fali Wang, Jihai Chen, Shuhua Yang, Runxue Bao, Tianxiang Zhao, Zhiwei Zhang, Xianfeng Tang, Hui Liu, Qi He, Suhang Wang
2025	J	`jnl`	Skin-R1: Toward Trustworthy Clinical Reasoning for Dermatological Diagnosis. CoRR Zehao Liu, Wejieying Ren, Jipeng Zhang, Tianxiang Zhao, Jingxi Zhu, Xiaoting Li, Vasant G. Honavar
2025	—	`conf`	SmGNN: Link Prediction in Sparse Layers of Multi-layer Graphs. WebSci Huaisheng Zhu, Tianxiang Zhao, Zongyu Wu, Suhang Wang
2025	A	`conf`	Towards Reliable GNNs: Adversarial Calibration Learning for Confidence Estimation. CIKM Yilong Wang, Jiahao Zhang, Tianxiang Zhao, Suhang Wang
2024	J	`jnl`	A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. Mach. Intell. Res. Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
2024	—	`conf`	AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph. ASONAM (1) Huaisheng Zhu, Zongyu Wu, Tianxiang Zhao, Suhang Wang
2024	J	`jnl`	Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. CoRR Weijieying Ren, Xinlong Li, Lei Wang, Tianxiang Zhao, Wei Qin
2024	A*	`conf`	Disambiguated Node Classification with Graph Neural Networks. WWW Tianxiang Zhao, Xiang Zhang, Suhang Wang
2024	J	`jnl`	Disambiguated Node Classification with Graph Neural Networks. CoRR Tianxiang Zhao, Xiang Zhang, Suhang Wang
2024	A	`conf`	Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. WSDM Fali Wang, Tianxiang Zhao, Suhang Wang
2024	J	`jnl`	Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. CoRR Fali Wang, Tianxiang Zhao, Suhang Wang
2024	J	`jnl`	Enhance Graph Alignment for Large Language Models. CoRR Haitong Luo, Xuying Meng, Suhang Wang, Tianxiang Zhao, Fali Wang, Hanyun Cao, Yujun Zhang
2024	J	`jnl`	Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. CoRR Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang
2024	B	`conf`	Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models. IEEE Big Data Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang
2024	A	`conf`	HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CIKM Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang
2024	J	`jnl`	HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CoRR Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang
2024	J	`jnl`	Imbalanced Node Classification With Synthetic Over-Sampling. IEEE Trans. Knowl. Data Eng. Tianxiang Zhao, Xiang Zhang, Suhang Wang
2024	A	`conf`	Interpretable Imitation Learning with Dynamic Causal Relations. WSDM Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
2024	A*	`conf`	Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2024	J	`jnl`	Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2024	J	`jnl`	Towards Inductive and Efficient Explanations for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Dongsheng Luo, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Wenchao Yu, Xiao Liu, Haifeng Chen, Xiang Zhang
2023	J	`jnl`	Dynamic DAG Discovery for Interpretable Imitation Learning. CoRR Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
2023	J	`jnl`	Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2023	J	`jnl`	Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2023	A*	`conf`	Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. KDD Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
2023	J	`jnl`	Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. CoRR Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
2023	A	`conf`	T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. CIKM Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu
2023	J	`jnl`	T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. CoRR Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu
2023	A	`conf`	Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2023	—	`conf`	You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. PAKDD (2) Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang
2022	J	`jnl`	A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
2022	A	`conf`	Explanation Guided Contrastive Learning for Sequential Recommendation. CIKM Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao
2022	J	`jnl`	Explanation Guided Contrastive Learning for Sequential Recommendation. CoRR Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao
2022	A*	`conf`	Exploring Edge Disentanglement for Node Classification. WWW Tianxiang Zhao, Xiang Zhang, Suhang Wang
2022	J	`jnl`	Exploring Edge Disentanglement for Node Classification. CoRR Tianxiang Zhao, Xiang Zhang, Suhang Wang
2022	J	`jnl`	On Consistency in Graph Neural Network Interpretation. CoRR Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2022	J	`jnl`	Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR Tianxiang Zhao, Xiang Zhang, Suhang Wang
2022	—	`conf`	TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2022	J	`jnl`	TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
2022	A	`conf`	Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang
2021	J	`jnl`	Fair and Effective Policing for Neighborhood Safety: Understanding and Overcoming Selection Biases. Frontiers Big Data Weijieying Ren, Kunpeng Liu, Tianxiang Zhao, Yanjie Fu
2021	A	`conf`	GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. WSDM Tianxiang Zhao, Xiang Zhang, Suhang Wang
2021	J	`jnl`	GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. CoRR Tianxiang Zhao, Xiang Zhang, Suhang Wang
2021	J	`jnl`	Semi-Supervised Graph-to-Graph Translation. CoRR Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang
2021	J	`jnl`	Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. CoRR Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai
2021	J	`jnl`	You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. CoRR Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang
2020	A*	`conf`	Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation. AAAI Tianxiang Zhao, Lemao Liu, Guoping Huang, Huayang Li, Yingling Liu, Guiquan Liu, Shuming Shi
2020	—	`conf`	Emotion Embedded Pose Generation. ECCV Workshops (1) Amogh Subbakrishna Adishesha, Tianxiang Zhao
2020	A	`conf`	Semi-Supervised Graph-to-Graph Translation. CIKM Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang