| Fairness in graph mining: A survey Y Dong, J Ma, S Wang, C Chen, J Li IEEE Transactions on Knowledge and Data Engineering 35 (10), 10583-10602, 2023 | 138 | 2023 |
| Large Language Models for Data Annotation and Synthesis: A Survey Z Tan*, D Li*, S Wang*, A Beigi, B Jiang, A Bhattacharjee, M Karami, J Li, ... Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 120* | 2024 |
| Knowledge Editing for Large Language Models: A Survey S Wang, Y Zhu, H Liu, Z Zheng, C Chen, J Li ACM Computing Surveys, 2023 | 103 | 2023 |
| Reform: Error-aware few-shot knowledge graph completion S Wang, X Huang, C Chen, L Wu, J Li Proceedings of the 30th ACM international conference on information …, 2021 | 58 | 2021 |
| Hierarchical heterogeneous graph representation learning for short text classification Y Wang, S Wang, Q Yao, D Dou EMNLP, 2021 | 53 | 2021 |
| Task-adaptive few-shot node classification S Wang, K Ding, C Zhang, C Chen, J Li Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 51 | 2022 |
| On structural explanation of bias in graph neural networks Y Dong, S Wang, Y Wang, T Derr, J Li Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 35 | 2022 |
| Interpreting unfairness in graph neural networks via training node attribution Y Dong, S Wang, J Ma, N Liu, J Li Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7441-7449, 2023 | 32 | 2023 |
| Transductive linear probing: A novel framework for few-shot node classification Z Tan*, S Wang*, K Ding*, J Li, H Liu Learning on Graphs Conference, 4: 1-4: 21, 2022 | 27 | 2022 |
| Faith: Few-shot graph classification with hierarchical task graphs S Wang, Y Dong, X Huang, C Chen, J Li IJCAI, 2022 | 25 | 2022 |
| Federated few-shot learning S Wang, X Fu, K Ding, C Chen, H Chen, J Li Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 24 | 2023 |
| Graph few-shot learning with task-specific structures S Wang, C Chen, J Li Advances in Neural Information Processing Systems 35, 38925-38936, 2022 | 20 | 2022 |
| Interpreting pretrained language models via concept bottlenecks Z Tan, L Cheng, S Wang, B Yuan, J Li, H Liu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 56-74, 2024 | 19 | 2024 |
| Noise-robust fine-tuning of pretrained language models via external guidance S Wang, Z Tan, R Guo, J Li EMNLP Findings, 2023 | 19 | 2023 |
| Few-shot node classification with extremely weak supervision S Wang, Y Dong, K Ding, C Chen, J Li Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 19 | 2023 |
| Recognizing medical search query intent by few-shot learning Y Wang*, S Wang*, Y Li, D Dou Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 18 | 2022 |
| Contrastive meta-learning for few-shot node classification S Wang*, Z Tan*, H Liu, J Li Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 13 | 2023 |
| Knowledge Graph-Enhanced Large Language Models via Path Selection H Liu, S Wang, Y Zhu, Y Dong, J Li ACL Findings, 2024 | 12 | 2024 |
| Safety in Graph Machine Learning: Threats and Safeguards S Wang, Y Dong, B Zhang, Z Chen, X Fu, Y He, C Shen, C Zhang, ... arXiv preprint arXiv:2405.11034, 2024 | 12 | 2024 |
| Label-guided learning for text classification X Liu, S Wang, X Zhang, X You, J Wu, D Dou arXiv preprint arXiv:2002.10772, 2020 | 11 | 2020 |
Jundong LiAssistant Professor, University of VirginiaZweryfikowany adres z virginia.edu