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Reinforcement Learning for Mapping Instructions to Actions
S.R.K. Branavan
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Harr Chen
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Luke Zettlemoyer
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Regina Barzilay
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Paper Details:
Month: August
Year: 2009
Location: Suntec, Singapore
Venue:
ACL |
IJCNLP |
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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Bootstrapping Semantic Parsers from Conversations
Yoav Artzi
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Luke Zettlemoyer
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Unsupervised PCFG Induction for Grounded Language Learning with Highly Ambiguous Supervision
Joohyun Kim
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Raymond Mooney
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Inducing Document Plans for Concept-to-Text Generation
Ioannis Konstas
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Mirella Lapata
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Multi-Resolution Language Grounding with Weak Supervision
R. Koncel-Kedziorski
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Hannaneh Hajishirzi
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Ali Farhadi
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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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Fear the REAPER: A System for Automatic Multi-Document Summarization with Reinforcement Learning
Cody Rioux
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Sadid A. Hasan
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Yllias Chali
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Mise en Place: Unsupervised Interpretation of Instructional Recipes
Chloé Kiddon
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Ganesa Thandavam Ponnuraj
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Luke Zettlemoyer
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Yejin Choi
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Alignment-Based Compositional Semantics for Instruction Following
Jacob Andreas
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Dan Klein
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Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads
Ji He
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Mari Ostendorf
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Xiaodong He
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Jianshu Chen
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Jianfeng Gao
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Lihong Li
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Li Deng
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Mapping Instructions and Visual Observations to Actions with Reinforcement Learning
Dipendra Misra
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John Langford
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Yoav Artzi
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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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Mapping natural language commands to web elements
Panupong Pasupat
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Tian-Shun Jiang
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Evan Liu
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Kelvin Guu
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Percy Liang
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Grounding Language by Continuous Observation of Instruction Following
Ting Han
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David Schlangen
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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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Using Semantic Unification to Generate Regular Expressions from Natural Language
Nate Kushman
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Regina Barzilay
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Natural Language Communication with Robots
Yonatan Bisk
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Deniz Yuret
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Daniel Marcu
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Unified Pragmatic Models for Generating and Following Instructions
Daniel Fried
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Jacob Andreas
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Dan Klein
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Learning with Latent Language
Jacob Andreas
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Dan Klein
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Sergey Levine
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An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols
Chaitanya Kulkarni
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Wei Xu
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Alan Ritter
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Raghu Machiraju
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Learning to Follow Navigational Directions
Adam Vogel
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Daniel Jurafsky
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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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Confidence Driven Unsupervised Semantic Parsing
Dan Goldwasser
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Roi Reichart
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James Clarke
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Dan Roth
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Learning High-Level Planning from Text
S.R.K. Branavan
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Nate Kushman
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Tao Lei
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Regina Barzilay
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Spice it up? Mining Refinements to Online Instructions from User Generated Content
Gregory Druck
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Bo Pang
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Corpus-based Interpretation of Instructions in Virtual Environments
Luciana Benotti
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Martín Villalba
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Tessa Lau
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Julián Cerruti
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Models of Semantic Representation with Visual Attributes
Carina Silberer
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Vittorio Ferrari
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Mirella Lapata
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From Natural Language Specifications to Program Input Parsers
Tao Lei
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Fan Long
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Regina Barzilay
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Martin Rinard
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Lightly Supervised Learning of Procedural Dialog Systems
Svitlana Volkova
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Pallavi Choudhury
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Chris Quirk
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Bill Dolan
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Luke Zettlemoyer
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Learning to Automatically Solve Algebra Word Problems
Nate Kushman
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Yoav Artzi
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Luke Zettlemoyer
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Regina Barzilay
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Is this a wampimuk? Cross-modal mapping between distributional semantics and the visual world
Angeliki Lazaridou
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Elia Bruni
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Marco Baroni
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A Mapping-Based Approach for General Formal Human Computer Interaction Using Natural Language
Vincent Letard
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Sophie Rosset
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Gabriel Illouz
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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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Environment-Driven Lexicon Induction for High-Level Instructions
Dipendra Kumar Misra
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Kejia Tao
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Percy Liang
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Ashutosh Saxena
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Latent Predictor Networks for Code Generation
Wang Ling
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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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Learning Structured Predictors from Bandit Feedback for Interactive NLP
Artem Sokolov
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Julia Kreutzer
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Christopher Lo
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Stefan Riezler
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Deep Reinforcement Learning with a Natural Language Action Space
Ji He
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Jianshu Chen
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Xiaodong He
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Jianfeng Gao
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Lihong Li
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Li Deng
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Mari Ostendorf
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From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood
Kelvin Guu
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Panupong Pasupat
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Evan Liu
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Percy Liang
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Interactive Learning of Grounded Verb Semantics towards Human-Robot Communication
Lanbo She
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Joyce Chai
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Situated Mapping of Sequential Instructions to Actions with Single-step Reward Observation
Alane Suhr
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Yoav Artzi
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Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions
Yoav Artzi
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Luke Zettlemoyer
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Parsing entire discourses as very long strings: Capturing topic continuity in grounded language learning
Minh-Thang Luong
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Michael C. Frank
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Mark Johnson
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Large-scale Semantic Parsing without Question-Answer Pairs
Siva Reddy
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Mirella Lapata
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Mark Steedman
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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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Parsing Algebraic Word Problems into Equations
Rik Koncel-Kedziorski
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Hannaneh Hajishirzi
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Ashish Sabharwal
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Oren Etzioni
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Siena Dumas Ang
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Driving Semantic Parsing from the World’s Response
James Clarke
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Dan Goldwasser
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Ming-Wei Chang
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Dan Roth
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Learning to Interpret Natural Language Instructions
Monica Babeş-Vroman
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James MacGlashan
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Ruoyuan Gao
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Kevin Winner
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Richard Adjogah
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Marie desJardins
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Michael Littman
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Smaranda Muresan
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Toward Learning Perceptually Grounded Word Meanings from Unaligned Parallel Data
Stefanie Tellex
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Pratiksha Thaker
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Josh Joseph
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Nicholas Roy
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Grounding Language with Points and Paths in Continuous Spaces
Jacob Andreas
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Dan Klein
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Cooking with Semantics
Jonathan Malmaud
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Earl Wagner
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Nancy Chang
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Kevin Murphy
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From Shakespeare to Twitter: What are Language Styles all about?
Wei Xu
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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://groups.csail.mit.edu/rbg/code/rl/
Field Of Study
Approach
Unsupervised Learning
Language
English
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