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Maosong Sun
Maosong Sun
Professor of Computer Science and Technology, Tsinghua University
Verified email at tsinghua.edu.cn
Title
Cited by
Cited by
Year
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
61862020
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
44002015
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
16832019
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
13402015
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
12452016
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
8222016
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
7842015
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
6862018
Topical word embeddings
Y Liu, Z Liu, TS Chua, M Sun
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
5732015
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
5712019
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
5082015
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
5042010
Ptr: Prompt tuning with rules for text classification
X Han, W Zhao, N Ding, Z Liu, M Sun
AI Open 3, 182-192, 2022
4542022
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
4352009
Parameter-efficient fine-tuning of large-scale pre-trained language models
N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su, S Hu, Y Chen, CM Chan, ...
Nature Machine Intelligence 5 (3), 220-235, 2023
4252023
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
4172017
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
4172014
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
4142019
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
4102018
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
4102015
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