Dependency Grammar Induction with Neural Lexicalization and Big Training Data

Breaking out of local optima with count transforms and model recombination: A study in grammar induction

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Feature-rich part-of-speech tagging with a cyclic dependency network

Kristina Toutanova, Dan Klein, Christopher D Manning, and Yoram Singer. 2003 · 2003

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Corpus-based induction of syntactic structure: Models of dependency and constituency

Dan Klein and Christopher D. Manning. 2004 · 2004

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Inductive dependency parsing

Joakim Nivre. 2006 · 2006

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Logistic normal priors for unsupervised probabilistic grammar induction

Shay B Cohen, Kevin Gimpel, and Noah A Smith. 2008 · 2008

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Improving unsupervised dependency parsing with richer contexts and smoothing

William P Headden III, Mark Johnson, and David McClosky. 2009 · 2009

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Online em for unsupervised models

Percy Liang and Dan Klein. 2009 · 2009

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Painless unsupervised learning with features

Taylor Berg-Kirkpatrick, Alexandre Bouchard-Côté, John DeNero, and Dan Klein. 2010 · 2010

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Unsupervised induction of tree substitution grammars for dependency parsing

Phil Blunsom and Trevor Cohn. 2010 · 2010

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Sparsity in dependency grammar induction

Jennifer Gillenwater, Kuzman Ganchev, Joao Graça, Fernando Pereira, and Ben Taskar. 2010 · 2010

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Using universal linguistic knowledge to guide grammar induction

Tahira Naseem, Harr Chen, Regina Barzilay, and Mark Johnson. 2010 · 2010

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Software Framework for Topic Modelling with Large Corpora

Radim Řehůřek and Petr Sojka. 2010 · 2010

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Unambiguity regularization for unsupervised learning of probabilistic grammars

Original

Kewei Tu and Vasant Honavar. 2012 · 2012

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Stop-probability estimates computed on a large corpus improve unsupervised dependency parsing

David Marecek and Milan Straka. 2013 · 2013

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Unsupervised dependency parsing: Let’s use supervised parsers

Original

Phong Le and Willem Zuidema. 2015 · 2015

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Unsupervised neural dependency parsing

Yong Jiang, Wenjuan Han, and Kewei Tu. 2016 · 2016

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Grammar induction from (lots of) words alone

John K Pate and Mark Johnson. 2016 · 2016

Later among the works it cites.