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 | 5659 | 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 | 4183 | 2015 |
ERNIE: Enhanced language representation with informative entities Z Zhang, X Han, Z Liu, X Jiang, M Sun, Q Liu Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 1582 | 2019 |
Network representation learning with rich text information. C Yang, Z Liu, D Zhao, M Sun, EY Chang Proceedings of the 24th International Conference on Artificial Intelligence …, 2015 | 1316 | 2015 |
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 | 1214 | 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 | 788 | 2016 |
Modeling relation paths for representation learning of knowledge bases Y Lin, Z Liu, H Luan, M Sun, S Rao, S Liu Proceedings of the 2015 Conference on Empirical Methods in Natural Language …, 2015 | 757 | 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 Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 640 | 2018 |
Topical word embeddings Y Liu, Z Liu, TS Chua, M Sun Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 567 | 2015 |
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 Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 509 | 2019 |
Minimum risk training for neural machine translation S Shen, Y Cheng, Z He, W He, H Wu, M Sun, Y Liu Proceedings of the 54th Annual Meeting of the Association for Computational …, 2015 | 498 | 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 | 496 | 2010 |
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 | 432 | 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 | 414 | 2014 |
Ptr: Prompt tuning with rules for text classification X Han, W Zhao, N Ding, Z Liu, M Sun AI Open 3, 182-192, 2022 | 413 | 2022 |
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 | 404 | 2015 |
Iterative Entity Alignment via Joint Knowledge Embeddings. H Zhu, R Xie, Z Liu, M Sun Proceedings of the Twenty-Sixth International Joint Conference on Artificial …, 2017 | 400 | 2017 |
Word-level textual adversarial attacking as combinatorial optimization Y Zang, F Qi, C Yang, Z Liu, M Zhang, Q Liu, M Sun arXiv preprint arXiv:1910.12196, 2019 | 395 | 2019 |
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 | 395 | 2018 |
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 | 386 | 2016 |