Graphprompt: Unifying pre-training and downstream tasks for graph neural networks Z Liu, X Yu, Y Fang, X Zhang (Co-first author) Proceedings of the ACM Web Conference 2023, 417-428, 2023 | 72 | 2023 |
Learning to count isomorphisms with graph neural networks X Yu, Z Liu, Y Fang, X Zhang Proceedings of the AAAI Conference on Artificial Intelligence 2023, 4845-4853, 2023 | 14 | 2023 |
Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs X Yu, Z Liu, Y Fang, Z Liu, S Chen, X Zhang arXiv preprint arXiv:2311.15317, 2023 | 7 | 2023 |
HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-shot Prompt Learning X Yu, Z Liu, Y Fang, X Zhang Proceedings of the AAAI Conference on Artificial Intelligence 2024, 2023 | 6 | 2023 |
MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs X Yu, C Zhou, Y Fang, X Zhang Proceedings of the ACM Web Conference 2024, 2023 | 3 | 2023 |
Pixel adapter: A graph-based post-processing approach for scene text image super-resolution W Zhang, X Deng, B Jia, X Yu, Y Chen, J Ma, Q Ding, X Zhang Proceedings of the 31st ACM International Conference on Multimedia, 2168-2179, 2023 | 3 | 2023 |
Few-Shot Learning on Graphs: from Meta-learning to Pre-training and Prompting X Yu, Y Fang, Z Liu, Y Wu, Z Wen, J Bo, X Zhang, SCH Hoi arXiv preprint arXiv:2402.01440, 2024 | 1 | 2024 |
HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding P Xia, X Yu, M Hu, L Ju, Z Wang, P Duan, Z Ge arXiv preprint arXiv:2311.14064, 2023 | | 2023 |
Learning to Count Isomorphisms with Graph Neural Networks (Technical Appendices) X Yu, Z Liu, Y Fang, X Zhang | | 2023 |