| Rethinking Graph Neural Networks for Anomaly Detection J Tang, J Li, Z Gao, J Li ICML 2022, 2022 | 235 | 2022 |
| End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis L Xu, Q Zhou, K Gong, X Liang, J Tang, L Lin AAAI: The Thirty-Third AAAI Conference on Artificial Intelligence, 2019, 2019 | 184 | 2019 |
| Target-Guided Open-Domain Conversation J Tang, T Zhao, C Xiong, X Liang, EP Xing, Z Hu ACL: Annual meeting of the Association for Computational Linguistics, 2019, 2019 | 154 | 2019 |
| GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning J Chen*, J Tang*, J Qin, X Liang, L Liu, EP Xing, L Lin Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 | 143 | 2021 |
| MedDG: An Entity-Centric Medical Consultation Dataset for Entity-Aware Medical Dialogue Generation W Liu*, J Tang*, Y Cheng*, W Li, Y Zheng, X Liang CCF International Conference on Natural Language Processing and Chinese …, 2022 | 87* | 2022 |
| Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks J Qin, X Liang, Y Hong, J Tang, L Lin Association for Computational Linguistics (ACL-IJCNLP) 2021, 2021 | 64 | 2021 |
| Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation S Lin, P Zhou, X Liang, J Tang, R Zhao, Z Chen, L Lin The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI) 2021, 2020 | 59 | 2020 |
| GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection J Tang, F Hua, Z Gao, P Zhao, J Li NeurIPS 2023, 2023 | 51 | 2023 |
| Heterogeneous graph reasoning for knowledge-grounded medical dialogue system W Liu, J Tang, X Liang, Q Cai Neurocomputing 442, 260-268, 2021 | 39 | 2021 |
| Graphwiz: An instruction-following language model for graph computational problems N Chen*, Y Li*, J Tang*, J Li Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 36* | 2024 |
| Dynamic knowledge routing network for target-guided open-domain conversation J Qin, Z Ye, J Tang, X Liang Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8657-8664, 2020 | 36 | 2020 |
| A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment J Tang, K Zhao, J Li Findings of ACL 2023, 2023 | 24 | 2023 |
| Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport J Tang, W Zhang, J Li, K Zhao, F Tsung, J Li 39th IEEE International Conference on Data Engineering (ICDE) 2023, 2023 | 23 | 2023 |
| Handling Missing Data via Max-Entropy Regularized Graph Autoencoder Z Gao, Y Niu, J Cheng, J Tang, T Xu, P Zhao, L Li, F Tsung, J Li AAAI 2023, 2022 | 17 | 2022 |
| " My nose is running."" Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics W Liu, Y Cheng, H Wang, J Tang, Y Liu, R Zhao, W Li, Y Zheng, X Liang IJCAI 2022, 2022 | 16 | 2022 |
| A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data J Li, J Tang, L Kong, H Liu, J Li, AMC So, J Blanchet ICLR 2023, 2023 | 15* | 2023 |
| Grapharena: Benchmarking large language models on graph computational problems J Tang, Q Zhang, Y Li, J Li arXiv preprint arXiv:2407.00379, 2024 | 11 | 2024 |
| Outlier-Robust Gromov-Wasserstein for Graph Data L Kong, J Li, J Tang, AMC So NeurIPS 2023 (Spotlight), 2023 | 6 | 2023 |
| Data Imputation from the Perspective of Graph Dirichlet Energy W Zhang, G Li, J Tang, J Li, F Tsung CIKM 2024, 2024 | 4* | 2024 |
| 4dbinfer: A 4d benchmarking toolbox for graph-centric predictive modeling on relational dbs M Wang, Q Gan, D Wipf, Z Cai, N Li, J Tang, Y Zhang, Z Zhang, Z Mao, ... arXiv preprint arXiv:2404.18209, 2024 | 3 | 2024 |
Jia LiHKUST GuangzhouZweryfikowany adres z ust.hk