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Application of a Hybrid Bi-LSTM-CRF model to the task of Russian Named
  Entity Recognition
v1v2 (latest)

Application of a Hybrid Bi-LSTM-CRF model to the task of Russian Named Entity Recognition

27 September 2017
L. T. Anh
M. Y. Arkhipov
M. Burtsev
ArXiv (abs)PDFHTML

Papers citing "Application of a Hybrid Bi-LSTM-CRF model to the task of Russian Named Entity Recognition"

6 / 6 papers shown
Title
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
722
132,199
0
12 Jun 2017
NeuroNER: an easy-to-use program for named-entity recognition based on
  neural networks
NeuroNER: an easy-to-use program for named-entity recognition based on neural networks
Franck Dernoncourt
Ji Young Lee
Peter Szolovits
59
190
0
16 May 2017
Enriching Word Vectors with Subword Information
Enriching Word Vectors with Subword Information
Piotr Bojanowski
Edouard Grave
Armand Joulin
Tomas Mikolov
NAISSLVLM
229
9,978
0
15 Jul 2016
Neural Architectures for Named Entity Recognition
Neural Architectures for Named Entity Recognition
Guillaume Lample
Miguel Ballesteros
Sandeep Subramanian
Kazuya Kawakami
Chris Dyer
221
93
0
04 Mar 2016
Character-Aware Neural Language Models
Character-Aware Neural Language Models
Yoon Kim
Yacine Jernite
David Sontag
Alexander M. Rush
104
1,670
0
26 Aug 2015
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
575
27,325
0
01 Sep 2014
1