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The rise of neural networks, and particularly recurrent neural networks, has produced significant advances in part-of-speech tagging accuracy.
Bidirectional recurrent neural networks
Mike Schuster and Kuldip K Paliwal. 1997 · 1997
Earlier work this paper cites.
Fast and accurate part-of-speech tagging: The svm approach revisited
Jesús Giménez and Lluis Marquez. 2004 · 2004
Earlier work this paper cites.
Framewise phoneme classification with bidirectional lstm and other neural network architectures
Alex Graves and Jürgen Schmidhuber. 2005 · 2005
Earlier work this paper cites.
A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston. 2008 · 2008
Earlier work this paper cites.
Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011 · 2011
Earlier work this paper cites.
Semisupervised condensed nearest neighbor for part-of-speech tagging
Anders Søgaard. 2011 · 2011
Earlier work this paper cites.
A fast and accurate dependency parser using neural networks
Danqi Chen and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Learning character-level representations for part-of-speech tagging
Cicero D Santos and Bianca Zadrozny. 2014 · 2014
Earlier work this paper cites.
Improved transition-based parsing and tagging with neural networks
Chris Alberti, David Weiss, Greg Coppola, and Slav Petrov. 2015 · 2015
Cited alongside, same era.
Bidirectional LSTM-CRF models for sequence tagging http://arxiv.org/abs/1508.01991
Zhiheng Huang, Wei Xu, and Kai Yu. 2015 · 2015
Cited alongside, same era.
Finding function in form: Compositional character models for open vocabulary word representation
Wang Ling, Chris Dyer, Alan W Black, Isabel Trancoso, Ramon Fermandez, Silvio Amir, Luis Marujo, and Tiago Luis. 2015 · 2015
Cited alongside, same era.
A neural probabilistic structured-prediction model for transition-based dependency parsing
Hao Zhou, Yue Zhang, Shujian Huang, and Jiajun Chen. 2015 · 2015
Cited alongside, same era.
Globally normalized transition-based neural networks
Daniel Andor, Chris Alberti, David Weiss, Aliaksei Severyn, Alessandro Presta, Kuzman Ganchev, Slav Petrov, and Michael Collins. 2016 · 2016
Cited alongside, same era.
Stack-propagation: Improved representation learning for syntax
Yuan Zhang and David Weiss. 2016 · 2016
Later among the works it cites.
Syntaxnet models for the CoNLL 2017 shared task http://arxiv.org/abs/1703.04929
Chris Alberti, Daniel Andor, Ivan Bogatyy, Michael Collins, Dan Gillick, Lingpeng Kong, Terry Koo, Ji Ma, Mark Omernick, Slav Petrov, Chayut Thanapirom, Zora Tung, and David Weiss. 2017 · 2017
Later among the works it cites.
Ims at the CoNLL 2017 UD shared task: CRFs and perceptrons meet neural networks
Anders Björkelund, Agnieszka Falenska, Xiang Yu, and Jonas Kuhn. 2017 · 2017
Later among the works it cites.
Natural language processing with small feed-forward networks
Jan A. Botha, Emily Pitler, Ji Ma, Anton Bakalov, Alex Salcianu, David Weiss, Ryan McDonald, and Slav Petrov. 2017 · 2017
Later among the works it cites.
Stanford’s graph-based neural dependency parser at the CoNLL 2017 shared task
Timothy Dozat, Peng Qi, and Christopher D. Manning. 2017 · 2017
Later among the works it cites.
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A joint model for word embedding and word morphology
Kris Cao and Marek Rei. 2016 · 2016
Cited alongside, same era.
Dynamic Feature Induction: The Last Gist to the State-of-the-Art
Jinho D. Choi. 2016 · 2016
Cited alongside, same era.
Multilingual part-of-speech tagging with bidirectional long short-term memory models and auxiliary loss
Barbara Plank, Anders Søgaard, and Yoav Goldberg. 2016 · 2016
Cited alongside, same era.
Tokenizing, pos tagging, lemmatizing and parsing ud 2.0 with udpipe
Milan Straka and Jana Straková. 2017 · 2017
Later among the works it cites.
CoNLL 2017 shared task: Multilingual parsing from raw text to universal dependencies
Daniel Zeman, Martin Popel, Milan Straka, Jan Hajic, Joakim Nivre, Filip Ginter, Juhani Luotolahti, Sampo Pyysalo, Slav Petrov, Martin Potthast, Francis Tyers, Elena Badmaeva, Memduh Gokirmak, Anna Nedoluzhko, Silvie Cinkova, Jan Hajic jr., Jaroslava Hlavacova, Václava Kettnerová, Zdenka Uresova, Jenna Kanerva, Stina Ojala, Anna Missilä, Christopher D. Manning, Sebastian Schuster, Siva Reddy, Dima Taji, Nizar Habash, Herman Leung, Marie-Catherine de Marneffe, Manuela Sanguinetti, Maria Simi, Hiroshi Kanayama, Valeria dePaiva, Kira Droganova, Héctor Martínez Alonso, Çağrı Çöltekin, Umut Sulubacak, Hans Uszkoreit, Vivien Macketanz, Aljoscha Burchardt, Kim Harris, Katrin Marheinecke, Georg Rehm, Tolga Kayadelen, Mohammed Attia, Ali Elkahky, Zhuoran Yu, Emily Pitler, Saran Lertpradit, Michael Mandl, Jesse Kirchner, Hector Fernandez Alcalde, Jana Strnadová, Esha Banerjee, Ruli Manurung, Antonio Stella, Atsuko Shimada, Sookyoung Kwak, Gustavo Mendonca, Tatiana Lando, Rattima Nitisaroj, and Josie Li. 2017 · 2017
Later among the works it cites.
Deep contextualized word representations http://arxiv.org/abs/1802.05365
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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