Mo Yu
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A structured self-attentive sentence embedding
Z Lin, M Feng, CN Santos, M Yu, B Xiang, B Zhou, Y Bengio
arXiv preprint arXiv:1703.03130, 2017
Target-dependent twitter sentiment classification
L Jiang, M Yu, M Zhou, X Liu, T Zhao
Proceedings of the 49th annual meeting of the association for computational …, 2011
Comparative study of CNN and RNN for natural language processing
W Yin, K Kann, M Yu, H Schütze
arXiv preprint arXiv:1702.01923, 2017
DAG-GNN: DAG structure learning with graph neural networks
Y Yu, J Chen, T Gao, M Yu
International conference on machine learning, 7154-7163, 2019
R3: Reinforced Ranker-Reader for Open-Domain Question Answering
S Wang, M Yu, X Guo, Z Wang, T Klinger, W Zhang, S Chang, G Tesauro, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Improving lexical embeddings with semantic knowledge
M Yu, M Dredze
Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014
Improved neural relation detection for knowledge base question answering
M Yu, W Yin, KS Hasan, C Santos, B Xiang, B Zhou
arXiv preprint arXiv:1704.06194, 2017
Dilated recurrent neural networks
S Chang, Y Zhang, W Han, M Yu, X Guo, W Tan, X Cui, M Witbrock, ...
Advances in neural information processing systems 30, 2017
Diverse few-shot text classification with multiple metrics
M Yu, X Guo, J Yi, S Chang, S Potdar, Y Cheng, G Tesauro, H Wang, ...
arXiv preprint arXiv:1805.07513, 2018
Factor-based compositional embedding models
M Yu, M Gormley, M Dredze
NIPS workshop on learning semantics 411, 95-101, 2014
One-shot relational learning for knowledge graphs
W Xiong, M Yu, S Chang, X Guo, WY Wang
arXiv preprint arXiv:1808.09040, 2018
Differential treatment for stuff and things: A simple unsupervised domain adaptation method for semantic segmentation
Z Wang, M Yu, Y Wei, R Feris, J Xiong, W Hwu, TS Huang, H Shi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Cross-lingual knowledge graph alignment via graph matching neural network
K Xu, L Wang, M Yu, Y Feng, Y Song, Z Wang, D Yu
arXiv preprint arXiv:1905.11605, 2019
Image super-resolution via dual-state recurrent networks
W Han, S Chang, D Liu, M Yu, M Witbrock, TS Huang
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Simple question answering by attentive convolutional neural network
W Yin, M Yu, B Xiang, B Zhou, H Schütze
arXiv preprint arXiv:1606.03391, 2016
Invariant rationalization
S Chang, Y Zhang, M Yu, T Jaakkola
International Conference on Machine Learning, 1448-1458, 2020
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
S Wang, M Yu, J Jiang, W Zhang, X Guo, S Chang, Z Wang, T Klinger, ...
International Conference on Learning Representations (ICLR), 2018
Leveraging sentencelevel information with encoder lstm for natural language understanding
G Kurata, B Xiang, B Zhou, M Yu
arXiv preprint arXiv:1601.01530, 2016
Improving natural language inference using external knowledge in the science questions domain
X Wang, P Kapanipathi, R Musa, M Yu, K Talamadupula, I Abdelaziz, ...
Proceedings of the AAAI conference on artificial intelligence 33 (01), 7208-7215, 2019
Evidence integration for multi-hop reading comprehension with graph neural networks
L Song, Z Wang, M Yu, Y Zhang, R Florian, D Gildea
IEEE Transactions on Knowledge and Data Engineering 34 (2), 631-639, 2020
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