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ORCIDTianxiang Zhao 0001
Person information
- affiliation: Pennsylvania State University, State College, PA, USA
Other persons with the same name
- Tianxiang Zhao
- Tianxiang Zhao 0002
![[0009-0005-8783-5581]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0009-0005-8783-5581")
— Beijing University of Chemical Technology, Beijing, China - Tianxiang Zhao 0003 — Hangzhou Dianzi University, Hangzhou, China
- Tianxiang Zhao 0004 — Harbin Engineering University, Harbin, Heilongjiang, China
- Tianxiang Zhao 0005 — Ningbo University, Ningbo, China
- Tianxiang Zhao 0006 — University of Science and Technology of China, Anhui Province Key Laboratory of Big Data Analysis and Application, Hefei, China
- Tianxiang Zhao 0007 — Lanzhou University, School of Information Science & Engineering, China
- Tianxiang Zhao 0008 — Hong Kong University of Science and Technology (Guangzhou), China
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2020 – today
- 2026
[j6]Haitong Luo, Xuying Meng, Suhang Wang, Tianxiang Zhao, Fali Wang, Yujun Zhang:
Enhance graph alignment for large language models. Neural Networks 203: 109162 (2026)- [c25]Haitong Luo, Fali Wang, Weiyao Zhang, Xianren Zhang, Zhiwei Zhang, Tianxiang Zhao, Minhua Lin, Jiahao Zhang, Hui Liu, Xianfeng Tang, Qi He, Suhang Wang, Xuying Meng, Yujun Zhang:
Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic Limitations. ACL (Findings) 2026: 18936-18955 - [i29]Hanyang Wang, Weijieying Ren, Yuxiang Zhang, Ding Cao, Zhizhao Zeng, Ke Zeng, Tianxiang Zhao:
BiPACE: Bisimulation-Guided Policy Optimization with Action Counterfactual Estimation for LLM Agents. CoRR abs/2606.25556 (2026) - 2025
- [c24]Weijieying Ren, Tianxiang Zhao, Lei Wang, Tianchun Wang, Vasant G. Honavar:
DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. ACL (Findings) 2025: 25622-25635 - [c23]Yilong Wang, Jiahao Zhang, Tianxiang Zhao, Suhang Wang:
Towards Reliable GNNs: Adversarial Calibration Learning for Confidence Estimation. CIKM 2025: 3166-3176 - [c22]Xinlong Li, Weijieying Ren, Wei Qin, Lei Wang, Tianxiang Zhao, Richang Hong:
Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. ICASSP 2025: 1-5 - [c21]Huaisheng Zhu, Tianxiang Zhao, Zongyu Wu, Suhang Wang:
SmGNN: Link Prediction in Sparse Layers of Multi-layer Graphs. WebSci 2025: 484-493 - [c20]Yilong Wang, Tianxiang Zhao, Zongyu Wu, Suhang Wang:
Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs. WSDM 2025: 678-687 - [i28]Weijieying Ren, Tianxiang Zhao, Yuqing Huang, Vasant G. Honavar:
Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions. CoRR abs/2501.03540 (2025) - [i27]Yilong Wang, Jiahao Zhang, Tianxiang Zhao, Suhang Wang:
Enhance GNNs with Reliable Confidence Estimation via Adversarial Calibration Learning. CoRR abs/2503.18235 (2025) - [i26]Yilong Wang, Tianxiang Zhao, Zongyu Wu, Suhang Wang:
Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs. CoRR abs/2505.24055 (2025) - [i25]Weijieying Ren, Tianxiang Zhao, Lei Wang, Tianchun Wang, Vasant G. Honavar:
DiaLLMs: EHR Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. CoRR abs/2506.20059 (2025) - [i24]Weijieying Ren, Jingxi Zhu, Zehao Liu, Tianxiang Zhao, Vasant G. Honavar:
A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models. CoRR abs/2507.12774 (2025) - [i23]Fali Wang, Jihai Chen, Shuhua Yang, Runxue Bao, Tianxiang Zhao, Zhiwei Zhang, Xianfeng Tang, Hui Liu, Qi He, Suhang Wang:
Generalizing Test-time Compute-optimal Scaling as an Optimizable Graph. CoRR abs/2511.00086 (2025) - [i22]Zehao Liu, Wejieying Ren, Jipeng Zhang, Tianxiang Zhao, Jingxi Zhu, Xiaoting Li, Vasant G. Honavar:
Skin-R1: Toward Trustworthy Clinical Reasoning for Dermatological Diagnosis. CoRR abs/2511.14900 (2025) - 2024
- [j5]Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. Mach. Intell. Res. 21(6): 1011-1061 (2024) - [j4]Dongsheng Luo, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Wenchao Yu, Xiao Liu, Haifeng Chen, Xiang Zhang:
Towards Inductive and Efficient Explanations for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5245-5259 (2024) - [j3]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Imbalanced Node Classification With Synthetic Over-Sampling. IEEE Trans. Knowl. Data Eng. 36(12): 8515-8528 (2024) - [c19]Huaisheng Zhu, Zongyu Wu, Tianxiang Zhao, Suhang Wang:
AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph. ASONAM (1) 2024: 472-488 - [c18]Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang:
Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models. IEEE Big Data 2024: 741-746 - [c17]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CIKM 2024: 2326-2335 - [c16]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD 2024: 4479-4489 - [c15]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. WSDM 2024: 712-720 - [c14]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Interpretable Imitation Learning with Dynamic Causal Relations. WSDM 2024: 967-975 - [c13]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. WWW 2024: 914-923 - [i21]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. CoRR abs/2401.10394 (2024) - [i20]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. CoRR abs/2402.08824 (2024) - [i19]Weijieying Ren, Xinlong Li, Lei Wang, Tianxiang Zhao, Wei Qin:
Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. CoRR abs/2402.18865 (2024) - [i18]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR abs/2406.10425 (2024) - [i17]Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang:
Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. CoRR abs/2407.13989 (2024) - [i16]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CoRR abs/2407.17787 (2024) - [i15]Haitong Luo, Xuying Meng, Suhang Wang, Tianxiang Zhao, Fali Wang, Hanyun Cao, Yujun Zhang:
Enhance Graph Alignment for Large Language Models. CoRR abs/2410.11370 (2024) - 2023
- [j2]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. 14(5): 92:1-92:23 (2023) - [c12]Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu:
T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. CIKM 2023: 4244-4248 - [c11]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. KDD 2023: 3513-3524 - [c10]Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang:
You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. PAKDD (2) 2023: 40-52 - [c9]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM 2023: 634-642 - [i14]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR abs/2301.02791 (2023) - [i13]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. CoRR abs/2306.07919 (2023) - [i12]Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu:
T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. CoRR abs/2309.02610 (2023) - [i11]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Dynamic DAG Discovery for Interpretable Imitation Learning. CoRR abs/2310.00489 (2023) - 2022
- [c8]Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao:
Explanation Guided Contrastive Learning for Sequential Recommendation. CIKM 2022: 2017-2027 - [c7]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG 2022: 37 - [c6]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM 2022: 1433-1442 - [c5]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. WWW 2022: 1028-1036 - [i10]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. CoRR abs/2202.11245 (2022) - [i9]Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR abs/2204.08570 (2022) - [i8]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
On Consistency in Graph Neural Network Interpretation. CoRR abs/2205.13733 (2022) - [i7]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR abs/2206.05335 (2022) - [i6]Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao:
Explanation Guided Contrastive Learning for Sequential Recommendation. CoRR abs/2209.01347 (2022) - [i5]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR abs/2212.08689 (2022) - 2021
- [j1]Weijieying Ren, Kunpeng Liu, Tianxiang Zhao, Yanjie Fu:
Fair and Effective Policing for Neighborhood Safety: Understanding and Overcoming Selection Biases. Frontiers Big Data 4: 787459 (2021) - [c4]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. WSDM 2021: 833-841 - [i4]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. CoRR abs/2103.08826 (2021) - [i3]Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang:
Semi-Supervised Graph-to-Graph Translation. CoRR abs/2103.08827 (2021) - [i2]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. CoRR abs/2104.14537 (2021) - [i1]Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai:
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. CoRR abs/2105.13399 (2021) - 2020
- [c3]Tianxiang Zhao, Lemao Liu, Guoping Huang, Huayang Li, Yingling Liu, Guiquan Liu, Shuming Shi:
Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation. AAAI 2020: 9660-9667 - [c2]Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang:
Semi-Supervised Graph-to-Graph Translation. CIKM 2020: 1863-1872 - [c1]Amogh Subbakrishna Adishesha, Tianxiang Zhao:
Emotion Embedded Pose Generation. ECCV Workshops (1) 2020: 774-787
Coauthor Index
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