| Empower text-attributed graphs learning with large language models (llms) J Yu, Y Ren, C Gong, J Tan, X Li, X Zhang arXiv preprint arXiv:2310.09872, 2023 | 11 | 2023 |
| Prompt tuning for multi-view graph contrastive learning C Gong, X Li, J Yu, C Yao, J Tan, C Yu, D Yin arXiv preprint arXiv:2310.10362, 2023 | 4 | 2023 |
| Heterogeneous graph contrastive learning with meta-path contexts and weighted negative samples J Yu, X Li Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 3 | 2023 |
| Heterogeneous Graph Contrastive Learning with Meta-Path Contexts and Adaptively Weighted Negative Samples J Yu, Q Ge, X Li, A Zhou IEEE Transactions on Knowledge and Data Engineering, 2024 | 1 | 2024 |
| Context-Aware Session-Based Recommendation with Graph Neural Networks Z Zhang, J Yu, X Li 2023 IEEE International Conference on Knowledge Graph (ICKG), 35-44, 2023 | | 2023 |
| Self-supervised Heterogeneous Graph Variational Autoencoders Y Zhao, J Yu, Y Cheng, C Yu, Y Liu, X Li, S Wang arXiv preprint arXiv:2311.07929, 2023 | | 2023 |
| Resist Label Noise with PGM for Graph Neural Networks Q Ge, J Yu, Z Zhao, X Li arXiv preprint arXiv:2311.02116, 2023 | | 2023 |
