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The meaning of a sentence is a function of the relations that hold between its words.
On the shortest arborescence of a directed graph
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David A Smith and Noah A Smith · 2007
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Better hypothesis testing for statistical machine translation: Controlling for optimizer instability
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Adaptive subgradient methods for online learning and stochastic optimization
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Learning phrase representations using RNN encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom · 2014
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Yoon Kim · 2014
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Adam: A method for stochastic optimization
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning · 2015
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Stanford neural machine translation systems for spoken language domains
Minh-Thang Luong and Christopher D Manning · 2015
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Dependency-based convolutional neural networks for sentence embedding
Mingbo Ma, Liang Huang, Bing Xing, and Bowen Zhou · 2015
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Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D. Manning · 2015
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Structured training for neural network Transition-Based parsing
DRAGNN: A transition-based framework for dynamically connected neural networks
Lingpeng Kong, Chris Alberti, Daniel Andor, Ivan Bogatyy, and David Weiss · 2017
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Yang Liu and Mirella Lapata · 2017
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Neural probabilistic model for non-projective mst parsing
Xuezhe Ma and Eduard Hovy · 2017
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Jointly learning sentence embeddings and syntax with unsupervised tree-lstms
Jean Maillard, Stephen Clark, and Dani Yogatama · 2017
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Encoding sentences with graph convolutional networks for semantic role labeling
Diego Marcheggiani and Ivan Titov · 2017
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David Weiss, Chris Alberti, Michael Collins, and Slav Petrov · 2015
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Long short-term memory-networks for machine reading
Jianpeng Cheng, Li Dong, and Mirella Lapata · 2016
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
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Universal dependencies v1: A multilingual treebank collection
Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Yoav Goldberg, Jan Hajic, Christopher D Manning, Ryan T McDonald, Slav Petrov, Sampo Pyysalo, Natalia Silveira, and Others · 2016
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A decomposable attention model for natural language inference
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Graph convolutional encoders for syntax-aware neural machine translation
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Recurrent relational networks for complex relational reasoning
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A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Tim Lillicrap · 2017
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Modeling relational data with graph convolutional networks
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Neural paraphrase identification of questions with noisy pretraining
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Attention is all you need
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Bilateral multi-perspective matching for natural language sentences
Zhiguo Wang, Wael Hamza, and Radu Florian · 2017
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Learning to parse from a semantic objective: It works. is it syntax?
Adina Williams, Andrew Drozdov, and Samuel R Bowman · 2017
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Learning to compose words into sentences with reinforcement learning
Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, and Wang Ling · 2017
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The neural noisy channel
Lei Yu, Phil Blunsom, Chris Dyer, Edward Grefenstette, and Tomás Kociský · 2017
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Towards neural phrase-based machine translation
Po-Sen Huang, Chong Wang, Sitao Huang, Dengyong Zhou, and Li Deng · 2018
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Reinforced self-attention network: a hybrid of hard and soft attention for sequence modeling
Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Sen Wang, and Chengqi Zhang · 2018
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