| Graph neural networks: A review of methods and applications J Zhou, G Cui, S Hu, Z Zhang, C Yang, Z Liu, L Wang, C Li, M Sun AI open 1, 57-81, 2020 | 3477 | 2020 |
| Learning entity and relation embeddings for knowledge graph completion Y Lin, Z Liu, M Sun, Y Liu, X Zhu Proceedings of the AAAI conference on artificial intelligence 29 (1), 2015 | 3348 | 2015 |
| Network representation learning with rich text information. C Yang, Z Liu, D Zhao, M Sun, EY Chang IJCAI 2015, 2111-2117, 2015 | 1160 | 2015 |
| ERNIE: Enhanced language representation with informative entities Z Zhang, X Han, Z Liu, X Jiang, M Sun, Q Liu arXiv preprint arXiv:1905.07129, 2019 | 1091 | 2019 |
| Neural relation extraction with selective attention over instances Y Lin, S Shen, Z Liu, H Luan, M Sun Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 1064 | 2016 |
| Representation learning of knowledge graphs with entity descriptions R Xie, Z Liu, J Jia, H Luan, M Sun Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 670 | 2016 |
| Modeling relation paths for representation learning of knowledge bases Y Lin, Z Liu, H Luan, M Sun, S Rao, S Liu arXiv preprint arXiv:1506.00379, 2015 | 653 | 2015 |
| Topical word embeddings Y Liu, Z Liu, TS Chua, M Sun Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 518 | 2015 |
| Automatic keyphrase extraction via topic decomposition Z Liu, W Huang, Y Zheng, M Sun Proceedings of the 2010 conference on empirical methods in natural language …, 2010 | 467 | 2010 |
| Minimum risk training for neural machine translation S Shen, Y Cheng, Z He, W He, H Wu, M Sun, Y Liu arXiv preprint arXiv:1512.02433, 2015 | 449 | 2015 |
| Fewrel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation X Han, H Zhu, P Yu, Z Wang, Y Yao, Z Liu, M Sun arXiv preprint arXiv:1810.10147, 2018 | 439 | 2018 |
| Clustering to find exemplar terms for keyphrase extraction Z Liu, P Li, Y Zheng, M Sun Proceedings of the 2009 conference on empirical methods in natural language …, 2009 | 410 | 2009 |
| A unified model for word sense representation and disambiguation X Chen, Z Liu, M Sun Proceedings of the 2014 conference on empirical methods in natural language …, 2014 | 390 | 2014 |
| Joint learning of character and word embeddings X Chen, L Xu, Z Liu, M Sun, H Luan Twenty-fourth international joint conference on artificial intelligence, 2015 | 369 | 2015 |
| Neural sentiment classification with user and product attention H Chen, M Sun, C Tu, Y Lin, Z Liu Proceedings of the 2016 conference on empirical methods in natural language …, 2016 | 332 | 2016 |
| Openke: An open toolkit for knowledge embedding X Han, S Cao, X Lv, Y Lin, Z Liu, M Sun, J Li Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 322 | 2018 |
| Representation learning of knowledge graphs with hierarchical types. R Xie, Z Liu, M Sun IJCAI 2016, 2965-2971, 2016 | 318 | 2016 |
| DocRED: A large-scale document-level relation extraction dataset Y Yao, D Ye, P Li, X Han, Y Lin, Z Liu, Z Liu, L Huang, J Zhou, M Sun arXiv preprint arXiv:1906.06127, 2019 | 313 | 2019 |
| Iterative Entity Alignment via Joint Knowledge Embeddings. H Zhu, R Xie, Z Liu, M Sun IJCAI 17, 4258-4264, 2017 | 309 | 2017 |
| Max-margin deepwalk: Discriminative learning of network representation. C Tu, W Zhang, Z Liu, M Sun IJCAI 2016, 3889-3895, 2016 | 307 | 2016 |
Zhiyuan LiuAssociate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
