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Syntactic constituency parsing is a fundamental problem in natural language processing and has been the subject of intensive research and engineering for decades.
A neural network for learning how to parse tree adjoining grammar
Zoubin Ghahramani · 1990
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Building a large annotated corpus of english: The penn treebank
Mitchell P. Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz · 1993
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Three generative, lexicalised models for statistical parsing
Michael Collins · 1997
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A linear observed time statistical parser based on maximum entropy models
Adwait Ratnaparkhi · 1997
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Accurate unlexicalized parsing
Dan Klein and Christopher D. Manning · 2003
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Inducing history representations for broad coverage statistical parsing
James Henderson · 2003
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Discriminative training of a neural network statistical parser
James Henderson · 2004
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Incremental parsing with the perceptron algorithm
Michael Collins and Brian Roark · 2004
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Ontonotes: The 90% solution
Eduard Hovy, Mitchell Marcus, Martha Palmer, Lance Ramshaw, and Ralph Weischedel · 2006
Earlier work this paper cites.
Questionbank: Creating a corpus of parse-annotated questions
John Judge, Aoife Cahill, and Josef van Genabith · 2006
Earlier work this paper cites.
Learning accurate, compact, and interpretable tree annotation
Slav Petrov, Leon Barrett, Romain Thibaux, and Dan Klein · 2006
Cited alongside, same era.
Effective self-training for parsing
David McClosky, Eugene Charniak, and Mark Johnson · 2006
Cited alongside, same era.
Constituent parsing with incremental sigmoid belief networks
Ivan Titov and James Henderson · 2007
Cited alongside, same era.
Self-training PCFG grammars with latent annotations across languages
Zhongqiang Huang and Mary Harper · 2009
Cited alongside, same era.
Products of random latent variable grammars
Slav Petrov · 2010
Cited alongside, same era.
Self-training with products of latent variable grammars
Zhongqiang Huang, Mary Harper, and Slav Petrov · 2010
Cited alongside, same era.
Generating sequences with recurrent neural networks
Alex Graves · 2013
Later among the works it cites.
Recurrent continuous translation models
Nal Kalchbrenner and Phil Blunsom · 2013
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc VV Le · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Addressing the rare word problem in neural machine translation
Thang Luong, Ilya Sutskever, Quoc V Le, Oriol Vinyals, and Wojciech Zaremba · 2014
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Deep learning for efficient discriminative parsing
Ronan Collobert · 2011
Cited alongside, same era.
Parsing natural scenes and natural language with recursive neural networks
Richard Socher, Cliff C Lin, Chris Manning, and Andrew Y Ng · 2011
Cited alongside, same era.
Overview of the 2012 shared task on parsing the web
Slav Petrov and Ryan McDonald · 2012
Cited alongside, same era.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
Cited alongside, same era.
Fast and accurate shift-reduce constituent parsing
Muhua Zhu, Yue Zhang, Wenliang Chen, Min Zhang, and Jingbo Zhu · 2013
Cited alongside, same era.
Sébastien Jean, Kyunghyun Cho, Roland Memisevic, and Yoshua Bengio · 2014
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Ambiguity-aware ensemble training for semi-supervised dependency parsing
Zhenghua Li, Min Zhang, and Wenliang Chen · 2014
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Sparser, better, faster gpu parsing
David Hall, Taylor Berg-Kirkpatrick, John Canny, and Dan Klein · 2014
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End-to-end continuous speech recognition using attention-based recurrent nn: First results
Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2014
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