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Neural sequence-to-sequence models provide a competitive approach to the task of mapping a question in natural language to an SQL query, also referred to as text-to-SQL generation.
Expanding the scope of the ATIS task: The ATIS-3 corpus
Michael Brown William Fisher Kate Hunicke-Smith David Pallett Christine Pao Alexander Rudnicky Deborah A. Dahl, Madeleine Bates and Elizabeth Shriber. 1994 · 1994
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A new algorithm for data compression
Philip Gage. 1994 · 1994
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Learning to parse database queries using inductive logic programming
John M. Zelle and Raymond J. Mooney. 1996 · 1996
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Modern natural language interfaces to databases: Composing statistical parsing with semantic tractability
Ana-Maria Popescu, Alex Armanasu, Oren Etzioni, David Ko, and Alexander Yates. 2004 · 2004
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Semantic parsing as machine translation
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Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Language to logical form with neural attention
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Learning a neural semantic parser from user feedback
Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, and Luke Zettlemoyer. 2017 · 2017
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Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017 · 2017
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Learning a neural semantic parser from user feedback
Alvin Cheung Jayant Krishnamurthy Srinivasan Iyer, Ioannis Konstas and Luke Zettlemoyer. 2017 · 2017
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Coarse-to-fine decoding for neural semantic parsing
Li Dong and Mirella Lapata. 2018 · 2018
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Improving text-to-sql evaluation methodology
Catherine Finegan-Dollak, Jonathan K Kummerfeld, Li Zhang, Karthik Ramanathan, Sesh Sadasivam, Rui Zhang, and Dragomir Radev. 2018 · 2018
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Robin Jia and Percy Liang. 2016 · 2016
Cited alongside, same era.
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