| A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal K Liang, L Meng, M Liu, Y Liu, W Tu, S Wang, S Zhou, X Liu, F Sun, K He IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (12), 9456 …, 2024 | 387* | 2024 |
| Kimi k2: Open agentic intelligence K Team, Y Bai, Y Bao, G Chen, J Chen, N Chen, R Chen, Y Chen, Y Chen, ... arXiv preprint arXiv:2507.20534, 2025 | 344 | 2025 |
| Deep graph clustering via dual correlation reduction Y Liu, W Tu, S Zhou, X Liu, L Song, X Yang, E Zhu Proceedings of the AAAI conference on artificial intelligence 36 (7), 7603-7611, 2022 | 314 | 2022 |
| Mole-bert: Rethinking pre-training graph neural networks for molecules J Xia, C Zhao, B Hu, Z Gao, C Tan, Y Liu, S Li, SZ Li The 11st International Conference on Learning Representations (ICLR-23), 2023 | 238 | 2023 |
| Simple Contrastive Graph Clustering Y Liu, X Yang, S Zhou, X Liu IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS), 2023 | 227 | 2023 |
| Cluster-guided Contrastive Graph Clustering Network X Yang, Y Liu, S Zhou, S Wang, W Tu, Q Zheng, X Liu, L Fang, E Zhu Proceedings of the 37th AAAI conference on artificial intelligence (AAAI-23), 2023 | 190 | 2023 |
| Hard Sample Aware Network for Contrastive Deep Graph Clustering Y Liu, X Yang, S Zhou, X Liu, Z Wang, K Liang, W Tu, L Li, J Duan, ... Proceedings of the 37th AAAI conference on artificial intelligence (AAAI-23), 2023 | 189 | 2023 |
| Knowledge Graph Contrastive Learning based on Relation-Symmetrical Structure K Liang, Y Liu, S Zhou, X Liu, W Tu IEEE Transactions on Knowledge and Data Engineering (IEEE T-KDE), 2023 | 179* | 2023 |
| Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View J Duan, S Wang, P Zhang, E Zhu, J Hu, H Jin, Y Liu, Z Dong Proceedings of the 37th AAAI conference on artificial intelligence (AAAI-23), 2023 | 167 | 2023 |
| Dealmvc: Dual contrastive calibration for multi-view clustering X Yang, J Jiaqi, S Wang, K Liang, Y Liu, Y Wen, S Liu, S Zhou, X Liu, ... The 31st ACM International Conference on Multimedia (ACMMM-23), 2023 | 164 | 2023 |
| A survey of deep graph clustering: Taxonomy, challenge, application, and open resource Y Liu, J Xia, S Zhou, X Yang, K Liang, C Fan, Y Zhuang, SZ Li, X Liu, K He arXiv preprint arXiv:2211.12875, 2022 | 140* | 2022 |
| Contrastive multi-view subspace clustering of hyperspectral images based on graph convolutional networks R Guan, Z Li, W Tu, J Wang, Y Liu, X Li, C Tang, R Feng IEEE Transactions on Geoscience and Remote Sensing (IEEE T-GRS), 2024 | 135 | 2024 |
| Learn from relational correlations and periodic events for temporal knowledge graph reasoning K Liang, L Meng, M Liu, Y Liu, W Tu, S Wang, S Zhou, X Liu The 46th international SIGIR conference (SIGIR-23), 1559-1568, 2023 | 130 | 2023 |
| Self-supervised temporal graph learning with temporal and structural intensity alignment M Liu, K Liang, Y Zhao, W Tu, S Zhou, X Gan, X Liu, K He IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS), 2024 | 120 | 2024 |
| Deep temporal graph clustering M Liu, Y Liu, K Liang, W Tu, S Wang, S Zhou, X Liu The 12th International Conference on Learning Representations (ICLR-24), 2024 | 111 | 2024 |
| Dink-Net: Neural Clustering on Large Graphs Y Liu, K Liang, J Xia, S Zhou, X Yang, X Liu, SZ Li The 40th International Conference on Machine Learning (ICML-23), 2023 | 87 | 2023 |
| Convert: Contrastive graph clustering with reliable augmentation X Yang, C Tan, Y Liu, K Liang, S Wang, S Zhou, J Xia, SZ Li, X Liu, E Zhu The 31st ACM International Conference on Multimedia (ACMMM-23), 319-327, 2023 | 78 | 2023 |
| Flipattack: Jailbreak llms via flipping Y Liu, X He, M Xiong, J Fu, S Deng, M Yingwei, Z Jiaheng, B Hooi The 42th International Conference on Machine Learning (ICML-25), 2025 | 77 | 2025 |
| A comprehensive survey in llm (-agent) full stack safety: Data, training and deployment K Wang, G Zhang, Z Zhou, J Wu, M Yu, S Zhao, C Yin, J Fu, Y Yan, H Luo, ... arXiv preprint arXiv:2504.15585, 2025 | 74 | 2025 |
| At Which Training Stage Does Code Data Help LLMs Reasoning? Y Ma*, Y Liu*, Y Yu, Y Zhang, Y Jiang, C Wang, S Li The 12nd International Conference on Learning Representations (ICLR-24), 2024 | 74 | 2024 |
Xinwang LiuSenior Member of IEEE and CCF, NUDTVerified email at nudt.edu.cn
