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BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
v1v2 (latest)

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

11 October 2018
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
    VLMSSLSSeg
ArXiv (abs)PDFHTML

Papers citing "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding"

17 / 33,017 papers shown
Title
Interact and Decide: Medley of Sub-Attention Networks for Effective
  Group Recommendation
Interact and Decide: Medley of Sub-Attention Networks for Effective Group Recommendation
Lucas Vinh Tran
T. Pham
Yi Tay
Yiding Liu
Gao Cong
Xiaoli Li
283
101
0
12 Apr 2018
Clinical Concept Embeddings Learned from Massive Sources of Multimodal
  Medical Data
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data
Andrew L. Beam
Benjamin Kompa
A. Schmaltz
Inbar Fried
G. Weber
N. Palmer
Xu Shi
Tianxi Cai
I. Kohane
107
194
0
04 Apr 2018
The Geometry of Culture: Analyzing Meaning through Word Embeddings
The Geometry of Culture: Analyzing Meaning through Word Embeddings
Austin C. Kozlowski
Matt Taddy
James A. Evans
155
432
0
25 Mar 2018
SparCML: High-Performance Sparse Communication for Machine Learning
SparCML: High-Performance Sparse Communication for Machine Learning
Cédric Renggli
Saleh Ashkboos
Mehdi Aghagolzadeh
Dan Alistarh
Torsten Hoefler
251
137
0
22 Feb 2018
Deep Learning for Genomics: A Concise Overview
Deep Learning for Genomics: A Concise Overview
Tianwei Yue
Yuanxin Wang
Longxiang Zhang
Chunming Gu
Haohan Wang
Wenping Wang
Qi Lyu
Yujie Dun
AILawVLMBDL
261
96
0
02 Feb 2018
DisSent: Sentence Representation Learning from Explicit Discourse
  Relations
DisSent: Sentence Representation Learning from Explicit Discourse Relations
Allen Nie
Erin D. Bennett
Noah D. Goodman
SSL
174
54
0
12 Oct 2017
Natural Language Processing: State of The Art, Current Trends and
  Challenges
Natural Language Processing: State of The Art, Current Trends and Challenges
Diksha Khurana
Aditya Koli
Kiran Khatter
Sukhdev Singh
138
1,332
0
17 Aug 2017
Simple and Effective Dimensionality Reduction for Word Embeddings
Simple and Effective Dimensionality Reduction for Word Embeddings
Vikas Raunak
182
110
0
11 Aug 2017
Recent Trends in Deep Learning Based Natural Language Processing
Recent Trends in Deep Learning Based Natural Language ProcessingIEEE Computational Intelligence Magazine (IEEE CIM), 2017
Tom Young
Devamanyu Hazarika
Soujanya Poria
Xiaoshi Zhong
640
2,982
0
09 Aug 2017
A Survey Of Cross-lingual Word Embedding Models
A Survey Of Cross-lingual Word Embedding Models
Sebastian Ruder
Ivan Vulić
Anders Søgaard
283
558
0
15 Jun 2017
Lifelong Generative Modeling
Lifelong Generative Modeling
Jason Ramapuram
Magda Gregorova
Alexandros Kalousis
BDLCLL
425
128
0
27 May 2017
Jointly Learning Sentence Embeddings and Syntax with Unsupervised
  Tree-LSTMs
Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs
Jean Maillard
S. Clark
Dani Yogatama
144
91
0
25 May 2017
A survey of embedding models of entities and relationships for knowledge
  graph completion
A survey of embedding models of entities and relationships for knowledge graph completion
Dat Quoc Nguyen
392
100
0
23 Mar 2017
Evolving Deep Neural Networks
Evolving Deep Neural Networks
Risto Miikkulainen
J. Liang
Elliot Meyerson
Aditya Rawal
Daniel Fink
...
B. Raju
Hormoz Shahrzad
Arshak Navruzyan
Nigel P. Duffy
Babak Hodjat
306
933
0
01 Mar 2017
Symbolic, Distributed and Distributional Representations for Natural
  Language Processing in the Era of Deep Learning: a Survey
Symbolic, Distributed and Distributional Representations for Natural Language Processing in the Era of Deep Learning: a SurveyFrontiers in Robotics and AI (Front. Robot. AI), 2017
L. Ferrone
Fabio Massimo Zanzotto
158
41
0
02 Feb 2017
Quantifying the probable approximation error of probabilistic inference
  programs
Quantifying the probable approximation error of probabilistic inference programs
Marco F. Cusumano-Towner
Vikash K. Mansinghka
197
9
0
31 May 2016
Impact of Power System Partitioning on the Efficiency of Distributed
  Multi-Step Optimization
Impact of Power System Partitioning on the Efficiency of Distributed Multi-Step Optimization
Dongliang Chen
A. Bucchiarone
Zhihan Lv
120
13
0
31 May 2016
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