| 21 |
The Best Lexical Metric for Phrase-Based Statistical MT System Optimization
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In: http://www.mt-archive.info/NAACL-HLT-2010-Cer-1.pdf (2010)
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| 22 |
Learning continuous phrase representations and syntactic parsing with recursive neural networks
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In: http://www.socher.org/uploads/Main/2010SocherManningNg.pdf (2010)
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| 23 |
Learning continuous phrase representations and syntactic parsing with recursive neural networks
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In: http://wuawua.googlecode.com/files/Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks.pdf (2010)
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| 24 |
Better Arabic parsing: Baselines, evaluations, and analysis
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In: http://aclweb.org/anthology-new/C/C10/C10-1045.pdf (2010)
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| 25 |
Better Arabic Parsing: Baselines, Evaluations, and Analysis
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In: http://www.spencegreen.com/pubs/green+manning.coling10.pdf (2010)
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| 26 |
Better Arabic parsing: Baselines, evaluations, and analysis
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In: http://nlp.stanford.edu/pubs/coling2010-arabic.pdf (2010)
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| 27 |
Subword variation in text message classification. Paper presented at the Human Language Technologies: The Annual Conference of the North American Chapter of the ACL
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In: http://mickey.ifp.illinois.edu/speechWiki/images/7/73/Munro-Manning_NAACL10.pdf (2010)
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| 28 |
Subword variation in text message classification
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In: http://nlp.stanford.edu/pubs/munro2010chichewa.pdf (2010)
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| 29 |
Phrasal: a toolkit for statistical machine translation with facilities for extraction and incorporation of arbitrary model features.
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In: https://www.microsoft.com/en-us/research/wp-content/uploads/2010/06/Phrasal-A-Statistical-Machine-Translation-Toolkit-for-Exploring-New-Model-Features.pdf (2010)
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| 30 |
Subword variation in text message classification
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In: http://www.aclweb.org/anthology-new/N/N10/N10-1075.pdf (2010)
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| 31 |
Probabilistic treeedit models with structured latent variables for textual entailment and question answering
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In: http://nlp.stanford.edu/pubs/wang-manning-coling10.pdf (2010)
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| 32 |
Disambiguating ”DE” for Chinese-English machine translation
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In: http://www.mt-archive.info/WMT-2009-Chang.pdf (2009)
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| 33 |
Disambiguating ”DE” for Chinese-English machine translation
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In: http://www.statmt.org/wmt09/pdf/WMT-0936.pdf (2009)
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| 34 |
Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates
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In: http://homepages.inf.ed.ac.uk/sgwater/papers/specom-erranal.pdf (2009)
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| 35 |
An extended model of natural logic
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In: http://aclweb.org/anthology-new/W/W09/W09-3714.pdf (2009)
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| 36 |
Textual entailment features for machine translation evaluation
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In: http://aclweb.org/anthology-new/W/W09/W09-0404.pdf (2009)
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| 37 |
NP subject detection in verb-initial Arabic clauses
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In: http://www.mt-archive.info/MTS-2009-Green.pdf (2009)
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| 38 |
Joint parsing and named entity recognition
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In: http://www.aclweb.org/anthology-new/N/N09/N09-1037.pdf (2009)
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| 39 |
Optimizing Chinese word segmentation for machine translation performance
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In: http://www.statmt.org/wmt08/pdf/WMT36.pdf (2008)
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| 40 |
Optimizing Chinese word segmentation for machine translation performance
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In: http://www.mt-archive.info/ACL-SMT-2008-Chang.pdf (2008)
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