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Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes
Chris Quirk
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Raymond Mooney
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Michel Galley
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Paper Details:
Month: July
Year: 2015
Location: Beijing, China
Venue:
ACL |
IJCNLP |
Citations
URL
From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems
Mrinmaya Sachan
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Kumar Dubey
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Eric Xing
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Mapping Language to Code in Programmatic Context
Srinivasan Iyer
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Ioannis Konstas
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Alvin Cheung
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Luke Zettlemoyer
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Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
Tao Yu
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Rui Zhang
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Kai Yang
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Michihiro Yasunaga
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Dongxu Wang
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Zifan Li
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James Ma
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Irene Li
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Qingning Yao
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Shanelle Roman
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Zilin Zhang
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Dragomir Radev
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TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation
Pengcheng Yin
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Graham Neubig
|
May I take your order? A Neural Model for Extracting Structured Information from Conversations
Baolin Peng
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Michael Seltzer
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Y.C. Ju
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Geoffrey Zweig
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Kam-Fai Wong
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A Parallel Corpus of Python Functions and Documentation Strings for Automated Code Documentation and Code Generation
Antonio Valerio Miceli Barone
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Rico Sennrich
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NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System
Xi Victoria Lin
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Chenglong Wang
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Luke Zettlemoyer
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Michael D. Ernst
|
Language to Logical Form with Neural Attention
Li Dong
|
Mirella Lapata
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Latent Predictor Networks for Code Generation
Wang Ling
|
Phil Blunsom
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Edward Grefenstette
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Karl Moritz Hermann
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Tomáš Kočiský
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Fumin Wang
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Andrew Senior
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Improved Semantic Parsers For If-Then Statements
I. Beltagy
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Chris Quirk
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Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems
Wang Ling
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Dani Yogatama
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Chris Dyer
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Phil Blunsom
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A Syntactic Neural Model for General-Purpose Code Generation
Pengcheng Yin
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Graham Neubig
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Learning Semantic Correspondences in Technical Documentation
Kyle Richardson
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Jonas Kuhn
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Confidence Modeling for Neural Semantic Parsing
Li Dong
|
Chris Quirk
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Mirella Lapata
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StructVAE: Tree-structured Latent Variable Models for Semi-supervised Semantic Parsing
Pengcheng Yin
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Chunting Zhou
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Junxian He
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Graham Neubig
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How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing
Abhilasha Ravichander
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Thomas Manzini
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Matthias Grabmair
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Graham Neubig
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Jonathan Francis
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Eric Nyberg
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http://ifttt.com
http://ifttt.com
http://ifttt.com
http://research.microsoft.com/lang2code/
Field Of Study
Linguistic Trends
Syntax
Task
Semantic Parsing
Question Answering
Language Generation
Machine Translation
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