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 | 99 | 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 | 47 | 2021 |
Knowledge Editing for Large Language Models: A Survey S Wang, Y Zhu, H Liu, Z Zheng, C Chen, J Li arXiv preprint arXiv:2310.16218, 2023 | 39 | 2023 |
Hierarchical heterogeneous graph representation learning for short text classification Y Wang, S Wang, Q Yao, D Dou arXiv preprint arXiv:2111.00180, 2021 | 39 | 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 | 32 | 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 | 28 | 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 | 24 | 2023 |
Large language models for data annotation: A survey Z Tan, A Beigi, S Wang, R Guo, A Bhattacharjee, B Jiang, M Karami, J Li, ... arXiv preprint arXiv:2402.13446, 2024 | 21 | 2024 |
Faith: Few-shot graph classification with hierarchical task graphs S Wang, Y Dong, X Huang, C Chen, J Li arXiv preprint arXiv:2205.02435, 2022 | 18 | 2022 |
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 | 16 | 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 | 15 | 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 | 13 | 2022 |
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 | 12 | 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 | 11 | 2024 |
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 | 9 | 2023 |
Noise-robust fine-tuning of pretrained language models via external guidance S Wang, Z Tan, R Guo, J Li arXiv preprint arXiv:2311.01108, 2023 | 7 | 2023 |
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 | 4 | 2023 |
Fair few-shot learning with auxiliary sets S Wang, J Ma, L Cheng, J Li ECAI 2023, 2517-2524, 2023 | 2 | 2023 |
Knowledge Graph-Enhanced Large Language Models via Path Selection H Liu, S Wang, Y Zhu, Y Dong, J Li arXiv preprint arXiv:2406.13862, 2024 | | 2024 |
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning Z Chen, S Wang, C Shen, J Li arXiv preprint arXiv:2406.03730, 2024 | | 2024 |