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Improving Chemical Named Entity Recognition in Patents with
  Contextualized Word Embeddings

Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings

5 July 2019
Zenan Zhai
Dat Quoc Nguyen
S. Akhondi
Camilo Thorne
Christian Druckenbrodt
Trevor Cohn
M. Gregory
Karin Verspoor
ArXiv (abs)PDFHTML

Papers citing "Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings"

14 / 14 papers shown
Title
Using Similarity Measures to Select Pretraining Data for NER
Using Similarity Measures to Select Pretraining Data for NER
Xiang Dai
Sarvnaz Karimi
Ben Hachey
Cécile Paris
81
50
0
01 Apr 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,324
0
11 Oct 2018
Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models
  for chemical and disease named entity recognition
Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition
Zenan Zhai
Dat Quoc Nguyen
Karin Verspoor
30
30
0
25 Aug 2018
AllenNLP: A Deep Semantic Natural Language Processing Platform
AllenNLP: A Deep Semantic Natural Language Processing Platform
Matt Gardner
Joel Grus
Mark Neumann
Oyvind Tafjord
Pradeep Dasigi
Nelson F. Liu
Matthew E. Peters
Michael Schmitz
Luke Zettlemoyer
VLM
97
1,283
0
20 Mar 2018
Deep contextualized word representations
Deep contextualized word representations
Matthew E. Peters
Mark Neumann
Mohit Iyyer
Matt Gardner
Christopher Clark
Kenton Lee
Luke Zettlemoyer
NAI
235
11,569
0
15 Feb 2018
"Found in Translation": Predicting Outcomes of Complex Organic Chemistry
  Reactions using Neural Sequence-to-Sequence Models
"Found in Translation": Predicting Outcomes of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models
P. Schwaller
T. Gaudin
D. Lanyi
C. Bekas
Teodoro Laino
88
281
0
13 Nov 2017
Learning to Plan Chemical Syntheses
Learning to Plan Chemical Syntheses
Marwin H. S. Segler
Mike Preuss
M. Waller
103
1,377
0
14 Aug 2017
Reporting Score Distributions Makes a Difference: Performance Study of
  LSTM-networks for Sequence Tagging
Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging
Nils Reimers
Iryna Gurevych
87
437
0
31 Jul 2017
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling
  Tasks
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks
Nils Reimers
Iryna Gurevych
94
292
0
21 Jul 2017
Improving Automated Patent Claim Parsing: Dataset, System, and
  Experiments
Improving Automated Patent Claim Parsing: Dataset, System, and Experiments
Mengke Hu
David Cinciruk
J. Walsh
31
16
0
05 May 2016
Neural Architectures for Named Entity Recognition
Neural Architectures for Named Entity Recognition
Guillaume Lample
Miguel Ballesteros
Sandeep Subramanian
Kazuya Kawakami
Chris Dyer
236
4,021
0
04 Mar 2016
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Xuezhe Ma
Eduard H. Hovy
124
2,659
0
04 Mar 2016
Bidirectional LSTM-CRF Models for Sequence Tagging
Bidirectional LSTM-CRF Models for Sequence Tagging
Zhiheng Huang
Wenyuan Xu
Kai Yu
188
4,035
0
09 Aug 2015
Distributed Representations of Words and Phrases and their
  Compositionality
Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov
Ilya Sutskever
Kai Chen
G. Corrado
J. Dean
NAIOCL
406
33,573
0
16 Oct 2013
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