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Reading to Learn: Constructing Features from Semantic Abstracts
Jacob Eisenstein
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James Clarke
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Dan Goldwasser
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Dan Roth
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Paper Details:
Month: August
Year: 2009
Location: Singapore
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
A Game-Theoretic Approach to Generating Spatial Descriptions
Dave Golland
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Percy Liang
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Dan Klein
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Learning to Solve Arithmetic Word Problems with Verb Categorization
Mohammad Javad Hosseini
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Hannaneh Hajishirzi
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Oren Etzioni
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Nate Kushman
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Language Understanding for Text-based Games using Deep Reinforcement Learning
Karthik Narasimhan
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Tejas Kulkarni
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Regina Barzilay
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Solving Geometry Problems: Combining Text and Diagram Interpretation
Minjoon Seo
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Hannaneh Hajishirzi
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Ali Farhadi
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Oren Etzioni
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Clint Malcolm
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Joint Concept Learning and Semantic Parsing from Natural Language Explanations
Shashank Srivastava
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Igor Labutov
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Tom Mitchell
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Learning to Learn Semantic Parsers from Natural Language Supervision
Igor Labutov
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Bishan Yang
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Tom Mitchell
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Learning Dependency-Based Compositional Semantics
Percy Liang
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Michael I. Jordan
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Dan Klein
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Learning to Relate Literal and Sentimental Descriptions of Visual Properties
Mark Yatskar
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Svitlana Volkova
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Asli Celikyilmaz
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Bill Dolan
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Luke Zettlemoyer
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Reading between the Lines: Learning to Map High-Level Instructions to Commands
S.R.K. Branavan
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Luke Zettlemoyer
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Regina Barzilay
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Learning to Win by Reading Manuals in a Monte-Carlo Framework
S.R.K. Branavan
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David Silver
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Regina Barzilay
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Learning Dependency-Based Compositional Semantics
Percy Liang
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Michael Jordan
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Dan Klein
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A Bayesian Model for Unsupervised Semantic Parsing
Ivan Titov
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Alexandre Klementiev
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Which Step Do I Take First? Troubleshooting with Bayesian Models
Annie Louis
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Mirella Lapata
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http://www.comlab.ox
Field Of Study
Linguistic Trends
Discourse
Syntax
Task
Semantic Parsing
Approach
Generative Model
Unsupervised Learning
Language
Chinese
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