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Previous work approaches the SQL-to-text generation task using vanilla Seq2Seq models, which may not fully capture the inherent graph-structured information in SQL query.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2009 · 2009
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Alkis Simitsis and Yannis Ioannidis. 2009 · 2009
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Explaining structured queries in natural language
Georgia Koutrika, Alkis Simitsis, and Yannis E Ioannidis. 2010 · 2010
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Graph kernels
S Vichy N Vishwanathan, Nicol N Schraudolph, Risi Kondor, and Karsten M Borgwardt. 2010 · 2010
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Deep sparse rectifier neural networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio. 2011 · 2011
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Sorry, i don’t speak sparql: translating sparql queries into natural language
Axel-Cyrille Ngonga Ngomo, Lorenz Bühmann, Christina Unger, Jens Lehmann, and Daniel Gerber. 2013 · 2013
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling. 2016 · 2016
Later among the works it cites.
A simple but tough-to-beat baseline for sentence embeddings
Sanjeev Arora, Yingyu Liang, and Tengyu Ma. 2017 · 2017
Later among the works it cites.
Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec. 2017 · 2017
Later among the works it cites.
Seq2sql: Generating structured queries from natural language using reinforcement learning
Victor Zhong, Caiming Xiong, and Richard Socher. 2017 · 2017
Later among the works it cites.
A graph-to-sequence model for amr-to-text generation
Linfeng Song, Yue Zhang, Zhiguo Wang, and Daniel Gildea. 2018 · 2018
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Tree-to-sequence attentional neural machine translation
Akiko Eriguchi, Kazuma Hashimoto, and Yoshimasa Tsuruoka. 2016 · 2016
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Jiatao Gu, Zhengdong Lu, Hang Li, and Victor OK Li. 2016 · 2016
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Word mover’s embedding: From word2vec to document embedding
Lingfei Wu, Ian E.H. Yen, Kun Xu, Fangli Xu, Avinash Balakrishnan, Pin-Yu Chen, Pradeep Ravikumar, and Michael J. Witbrock. 2018a
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D2ke: From distance to kernel and embedding
Lingfei Wu, Ian En-Hsu Yen, Fangli Xu, Pradeep Ravikuma, and Michael Witbrock. 2018b
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Graph2seq: Graph to sequence learning with attention-based neural networks
Kun Xu, Lingfei Wu, Zhiguo Wang, and Vadim Sheinin. 2018 · 2018
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Summarizing source code using a neural attention model
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