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Solving algebraic word problems requires executing a series of arithmetic operations---a program---to obtain a final answer.
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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Semantic parsing with bayesian tree transducers
Bevan Keeley Jones, Mark Johnson, and Sharon Goldwater. 2012 · 2012
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Semantic parsing as machine translation
Jacob Andreas, Andreas Vlachos, and Stephen Clark. 2013 · 2013
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Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013 · 2013
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Recurrent continuous translation models
Nal Kalchbrenner and Phil Blunsom. 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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Learning to solve arithmetic word problems with verb categorization
Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, and Nate Kushman. 2014 · 2014
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Learning to automatically solve algebra word problems
Nate Kushman, Yoav Artzi, Luke Zettlemoyer, and Regina Barzilay. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 2014 · 2014
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Language to code: Learning semantic parsers for if-this-then-that recipes
Chris Quirk, Raymond Mooney, and Michel Galley. 2015 · 2015
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Solving general arithmetic word problems
Subhro Roy and Dan Roth. 2015 · 2015
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Pointer networks
Oriol Vinyals, Meire Fortunato, and Navdeep Jaitly. 2015 · 2015
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Hybrid computing using a neural network with dynamic external memory
Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwińska, Sergio Gómez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou, Adrià Puigdomènech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, and Demis Hassabis. 2016 · 2016
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Generating visual explanations
Neural symbolic machines: Learning semantic parsers on freebase with weak supervision
Chen Liang, Jonathan Berant, Quoc Le, Kenneth D. Forbus, and Ni Lao. 2016 · 2016
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Latent predictor networks for code generation
Wang Ling, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, Andrew Senior, Fumin Wang, and Phil Blunsom. 2016 · 2016
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016
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Neural programmer: Inducing latent programs with gradient descent
Arvind Neelakantan, Quoc V. Le, and Ilya Sutskever. 2016 · 2016
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Neural programmer-interpreters
Scott E. Reed and Nando de Freitas. 2016 · 2016
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Equation parsing: Mapping sentences to grounded equations
Subhro Roy, Shyam Upadhyay, and Dan Roth. 2016 · 2016
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Lisa Anne Hendricks, Zeynep Akata, Marcus Rohrbach, Jeff Donahue, Bernt Schiele, and Trevor Darrell. 2016 · 2016
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Rationalizing neural predictions
Tao Lei, Regina Barzilay, and Tommi Jaakkola. 2016 · 2016
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Rationalization: A neural machine translation approach to generating natural language explanations
Brent Harrison, Upol Ehsan, and Mark O. Riedl. 2017 · 2017
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