| Tucker decomposition-based temporal knowledge graph completion P Shao, D Zhang, G Yang, J Tao, F Che, T Liu Knowledge-Based Systems 238, 107841, 2022 | 68 | 2022 |
| Parame: Regarding neural network parameters as relation embeddings for knowledge graph completion F Che, D Zhang, J Tao, M Niu, B Zhao Proceedings of the AAAI conference on artificial intelligence 34 (03), 2774-2781, 2020 | 56 | 2020 |
| Self-supervised graph representation learning via bootstrapping F Che, G Yang, D Zhang, J Tao, T Liu Neurocomputing 456, 88-96, 2021 | 23 | 2021 |
| Multi-aspect self-supervised learning for heterogeneous information network F Che, J Tao, G Yang, T Liu, D Zhang Knowledge-Based Systems 233, 107474, 2021 | 13 | 2021 |
| M2ixKG: Mixing for harder negative samples in knowledge graph F Che, J Tao Neural Networks 177, 106358, 2024 | 7 | 2024 |
| Multi-level graph contrastive learning P Shao, J Tao Neurocomputing 570, 127101, 2024 | 7 | 2024 |
| Adaptive pseudo-Siamese policy network for temporal knowledge prediction P Shao, T Liu, F Che, D Zhang, J Tao Neural Networks 160, 192-201, 2023 | 5 | 2023 |
| Knowledge graph enhanced recommender system Z Huai, J Tao, F Che, G Yang, D Zhang arXiv preprint arXiv:2112.09425, 2021 | 2 | 2021 |
| Can large language models understand uncommon meanings of common words? J Wu, F Che, X Zheng, S Zhang, R Jin, S Nie, P Shao, J Tao arXiv preprint arXiv:2405.05741, 2024 | | 2024 |
| KS-LLM: Knowledge Selection of Large Language Models with Evidence Document for Question Answering X Zheng, F Che, J Wu, S Zhang, S Nie, K Liu, J Tao arXiv preprint arXiv:2404.15660, 2024 | | 2024 |
