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Joshua 2.0: A Toolkit for Parsing-Based Machine Translation with Syntax, Semirings, Discriminative Training and Other Goodies
Zhifei Li
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Chris Callison-Burch
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Chris Dyer
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Juri Ganitkevitch
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Ann Irvine
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Sanjeev Khudanpur
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Lane Schwartz
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Wren Thornton
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Ziyuan Wang
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Jonathan Weese
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Omar Zaidan
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Paper Details:
Month: July
Year: 2010
Location: Uppsala, Sweden
Venue:
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Citations
URL
Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation
Juri Ganitkevitch
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Chris Callison-Burch
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Courtney Napoles
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Benjamin Van Durme
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Does more data always yield better translations?
Guillem Gascó
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Martha-Alicia Rocha
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Germán Sanchis-Trilles
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Jesús Andrés-Ferrer
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Francisco Casacuberta
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Faster and Smaller N-Gram Language Models
Adam Pauls
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Dan Klein
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A Joint Sequence Translation Model with Integrated Reordering
Nadir Durrani
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Helmut Schmid
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Alexander Fraser
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Are Two Heads Better than One? Crowdsourced Translation via a Two-Step Collaboration of Non-Professional Translators and Editors
Rui Yan
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Mingkun Gao
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Ellie Pavlick
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Chris Callison-Burch
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Joshua 3.0: Syntax-based Machine Translation with the Thrax Grammar Extractor
Jonathan Weese
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Juri Ganitkevitch
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Chris Callison-Burch
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Matt Post
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Adam Lopez
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Crisis MT: Developing A Cookbook for MT in Crisis Situations
William Lewis
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Robert Munro
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Stephan Vogel
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Joshua 5.0: Sparser, Better, Faster, Server
Matt Post
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Juri Ganitkevitch
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Luke Orland
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Jonathan Weese
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Yuan Cao
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Chris Callison-Burch
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http://cs.jhu.edu/
Field Of Study
Linguistic Trends
Syntax
Task
Machine Translation
Language
Chinese
Urdu
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