| Learning on Large-scale Text-attributed Graphs via Variational Inference J Zhao, M Qu, C Li, H Yan, Q Liu, R Li, X Xie, J Tang International Conference on Learning Representations (ICLR 2023), 2022 | 92 | 2022 |
| HousE: Knowledge Graph Embedding with Householder Parameterization R Li, J Zhao, C Li, D He, Y Wang, Y Liu, H Sun, S Wang, W Deng, Y Shen, ... International Conference on Machine Learning (ICML 2022), 13209-13224, 2022 | 42 | 2022 |
| A New Perspective on the Effects of Spectrum in Graph Neural Networks M Yang, Y Shen, R Li, H Qi, Q Zhang, B Yin International Conference on Machine Learning (ICML 2022), 25261-25279, 2022 | 28 | 2022 |
| Test-time training for graph neural networks Y Wang, C Li, W Jin, R Li, J Zhao, J Tang, X Xie arXiv preprint arXiv:2210.08813, 2022 | 13 | 2022 |
| A survey on the memory mechanism of large language model based agents Z Zhang, X Bo, C Ma, R Li, X Chen, Q Dai, J Zhu, Z Dong, JR Wen arXiv preprint arXiv:2404.13501, 2024 | 5 | 2024 |
| To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion R Li, X Chen, C Li, Y Shen, J Zhao, Y Wang, W Han, H Sun, W Deng, ... ACL 2023 Main Conference (Long Paper), 2023 | 3 | 2023 |
| Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization R Li, C Li, Y Shen, Z Zhang, X Chen ICML 2024, 2024 | | 2024 |
