Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation. - Tianxiang Zhao 001; Lemao Liu; Guoping Huang; Huayang Li; Yingling Liu; Guiquan Liu; Shuming Shi 001 (AAAI, 2020)

Semi-Supervised Graph-to-Graph Translation. - Tianxiang Zhao 001; Xianfeng Tang; Xiang Zhang 001; Suhang Wang (CIKM, 2020)

Emotion Embedded Pose Generation. - Amogh Subbakrishna Adishesha; Tianxiang Zhao 001 (ECCV Workshops (1), 2020)

GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. - Tianxiang Zhao 001; Xiang Zhang 001; Suhang Wang (WSDM, 2021)

You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. - Tianxiang Zhao 001; Enyan Dai; Kai Shu; Suhang Wang (CoRR, 2021)

Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. - Yuqing Hu 002; Xiaoyuan Cheng; Suhang Wang; Jianli Chen; Tianxiang Zhao 001; Enyan Dai (CoRR, 2021)

Fair and Effective Policing for Neighborhood Safety: Understanding and Overcoming Selection Biases. - Weijieying Ren; Kunpeng Liu 001; Tianxiang Zhao 001; Yanjie Fu (Frontiers Big Data, 2021)

Explanation Guided Contrastive Learning for Sequential Recommendation. - Lei Wang 185; Ee-Peng Lim; Zhiwei Liu 001; Tianxiang Zhao 001 (CIKM, 2022)

TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. - Tianxiang Zhao 001; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (LoG, 2022)

Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. - Tianxiang Zhao 001; Enyan Dai; Kai Shu; Suhang Wang (WSDM, 2022)

Exploring Edge Disentanglement for Node Classification. - Tianxiang Zhao 001; Xiang Zhang 001; Suhang Wang (WWW, 2022)

On Consistency in Graph Neural Network Interpretation. - Tianxiang Zhao 001; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (CoRR, 2022)

Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. - Tianxiang Zhao 001; Xiang Zhang 001; Suhang Wang (CoRR, 2022)

T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. - Weijieying Ren; Tianxiang Zhao 001; Wei Qin; Kunpeng Liu 001 (CIKM, 2023)

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. - Tianxiang Zhao 001; Wenchao Yu; Suhang Wang; Lu Wang 029; Xiang Zhang 001; Yuncong Chen; Yanchi Liu; Wei Cheng 002; Haifeng Chen (KDD, 2023)

You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. - Huaisheng Zhu; Xianfeng Tang; Tianxiang Zhao 001; Suhang Wang (PAKDD (2), 2023)

Towards Faithful and Consistent Explanations for Graph Neural Networks. - Tianxiang Zhao 001; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (WSDM, 2023)

Dynamic DAG Discovery for Interpretable Imitation Learning. - Tianxiang Zhao 001; Wenchao Yu; Suhang Wang; Lu Wang 029; Xiang Zhang 001; Yuncong Chen; Yanchi Liu; Wei Cheng 002; Haifeng Chen (CoRR, 2023)

Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. - Tianxiang Zhao 001; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (ACM Trans. Intell. Syst. Technol., 2023)

AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph. - Huaisheng Zhu; Zongyu Wu 001; Tianxiang Zhao 001; Suhang Wang (ASONAM (1), 2024)

Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models. - Quan Li; Tianxiang Zhao 001; Lingwei Chen; Junjie Xu; Suhang Wang (IEEE Big Data, 2024)

HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. - Fali Wang; Tianxiang Zhao 001; Junjie Xu; Suhang Wang (CIKM, 2024)

Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. - Tianxiang Zhao 001; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (KDD, 2024)

Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. - Fali Wang; Tianxiang Zhao 001; Suhang Wang (WSDM, 2024)

Interpretable Imitation Learning with Dynamic Causal Relations. - Tianxiang Zhao 001; Wenchao Yu; Suhang Wang; Lu Wang 029; Xiang Zhang 001; Yuncong Chen; Yanchi Liu; Wei Cheng 002; Haifeng Chen (WSDM, 2024)

Disambiguated Node Classification with Graph Neural Networks. - Tianxiang Zhao 001; Xiang Zhang 001; Suhang Wang (WWW, 2024)

Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. - Weijieying Ren; Xinlong Li; Lei Wang 185; Tianxiang Zhao 001; Wei Qin (CoRR, 2024)

Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. - Quan Li; Tianxiang Zhao 001; Lingwei Chen; Junjie Xu; Suhang Wang (CoRR, 2024)

Enhance Graph Alignment for Large Language Models. - Haitong Luo; Xuying Meng; Suhang Wang; Tianxiang Zhao 001; Fali Wang; Hanyun Cao; Yujun Zhang 001 (CoRR, 2024)

Towards Inductive and Efficient Explanations for Graph Neural Networks. - Dongsheng Luo; Tianxiang Zhao 001; Wei Cheng 002; Dongkuan Xu; Feng Han; Wenchao Yu; Xiao Liu 039; Haifeng Chen; Xiang Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. - Enyan Dai; Tianxiang Zhao 001; Huaisheng Zhu; Junjie Xu; Zhimeng Guo; Hui Liu 031; Jiliang Tang; Suhang Wang (Mach. Intell. Res., 2024)

Imbalanced Node Classification With Synthetic Over-Sampling. - Tianxiang Zhao 001; Xiang Zhang 001; Suhang Wang (IEEE Trans. Knowl. Data Eng., 2024)

DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. - Weijieying Ren; Tianxiang Zhao 001; Lei Wang 185; Tianchun Wang; Vasant G. Honavar (ACL (Findings), 2025)

Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. - Xinlong Li; Weijieying Ren; Wei Qin; Lei Wang 185; Tianxiang Zhao 001; Richang Hong (ICASSP, 2025)

SmGNN: Link Prediction in Sparse Layers of Multi-layer Graphs. - Huaisheng Zhu; Tianxiang Zhao 001; Zongyu Wu 001; Suhang Wang (WebSci, 2025)

Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs. - Yilong Wang 001; Tianxiang Zhao 001; Zongyu Wu 001; Suhang Wang (WSDM, 2025)

Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions. - Weijieying Ren; Tianxiang Zhao 001; Yuqing Huang; Vasant G. Honavar (CoRR, 2025)

Enhance GNNs with Reliable Confidence Estimation via Adversarial Calibration Learning. - Yilong Wang 001; Jiahao Zhang; Tianxiang Zhao 001; Suhang Wang (CoRR, 2025)

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models. - Weijieying Ren; Jingxi Zhu; Zehao Liu; Tianxiang Zhao 001; Vasant G. Honavar (CoRR, 2025)