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Structured Training for Neural Network Transition-Based Parsing

Structured Training for Neural Network Transition-Based Parsing

19 June 2015
David J. Weiss
Chris Alberti
Michael Collins
Slav Petrov
ArXiv (abs)PDFHTML

Papers citing "Structured Training for Neural Network Transition-Based Parsing"

30 / 80 papers shown
DRAGNN: A Transition-based Framework for Dynamically Connected Neural
  Networks
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks
Lingpeng Kong
Chris Alberti
D. Andor
Ivan Bogatyy
David J. Weiss
GNN
206
34
0
13 Mar 2017
Tackling Error Propagation through Reinforcement Learning: A Case of
  Greedy Dependency Parsing
Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency ParsingConference of the European Chapter of the Association for Computational Linguistics (EACL), 2017
Minh Le
Antske Fokkens
123
20
0
22 Feb 2017
Improving a Strong Neural Parser with Conjunction-Specific Features
Improving a Strong Neural Parser with Conjunction-Specific FeaturesConference of the European Chapter of the Association for Computational Linguistics (EACL), 2017
Jessica Ficler
Yoav Goldberg
122
7
0
22 Feb 2017
Fast and Accurate Entity Recognition with Iterated Dilated Convolutions
Fast and Accurate Entity Recognition with Iterated Dilated ConvolutionsConference on Empirical Methods in Natural Language Processing (EMNLP), 2017
Emma Strubell
Pat Verga
David Belanger
Andrew McCallum
384
420
0
07 Feb 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
Span-Based Constituency Parsing with a Structure-Label System and
  Provably Optimal Dynamic Oracles
Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic OraclesConference on Empirical Methods in Natural Language Processing (EMNLP), 2016
James Cross
Liang Huang
209
122
0
20 Dec 2016
Embedding Words and Senses Together via Joint Knowledge-Enhanced
  Training
Embedding Words and Senses Together via Joint Knowledge-Enhanced Training
Goran Frehse
Jose Camacho-Collados
Ignacio Iacobacci
Roberto Navigli
207
78
0
08 Dec 2016
Deep Biaffine Attention for Neural Dependency Parsing
Deep Biaffine Attention for Neural Dependency Parsing
Timothy Dozat
Christopher D. Manning
394
1,281
0
06 Nov 2016
A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
Kazuma Hashimoto
Caiming Xiong
Yoshimasa Tsuruoka
R. Socher
KELM
437
585
0
05 Nov 2016
An empirical study for Vietnamese dependency parsing
An empirical study for Vietnamese dependency parsing
Dat Quoc Nguyen
Mark Dras
Mark Johnson
125
15
0
03 Nov 2016
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser
A. Kuncoro
Miguel Ballesteros
Lingpeng Kong
Chris Dyer
Noah A. Smith
MoE
125
77
0
24 Sep 2016
Bi-directional Attention with Agreement for Dependency Parsing
Bi-directional Attention with Agreement for Dependency Parsing
Hao Cheng
Hao Fang
Xiaodong He
Jianfeng Gao
Li Deng
184
47
0
06 Aug 2016
Dependency Language Models for Transition-based Dependency Parsing
Dependency Language Models for Transition-based Dependency ParsingInternational Workshop/Conference on Parsing Technologies (IWPT), 2016
Juntao Yu
Bernd Bohnet
125
4
0
18 Jul 2016
Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs
Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMsConference on Computational Natural Language Learning (CoNLL), 2016
Swabha Swayamdipta
Miguel Ballesteros
Chris Dyer
Noah A. Smith
RALM
150
63
0
29 Jun 2016
Incremental Parsing with Minimal Features Using Bi-Directional LSTM
Incremental Parsing with Minimal Features Using Bi-Directional LSTM
James Cross
Liang Huang
189
88
0
21 Jun 2016
Dependency Parsing as Head Selection
Dependency Parsing as Head SelectionConference of the European Chapter of the Association for Computational Linguistics (EACL), 2016
Xingxing Zhang
Jianpeng Cheng
Mirella Lapata
450
95
0
03 Jun 2016
Exploiting Multi-typed Treebanks for Parsing with Deep Multi-task
  Learning
Exploiting Multi-typed Treebanks for Parsing with Deep Multi-task Learning
Jiang Guo
Wanxiang Che
Haifeng Wang
Ting Liu
100
21
0
03 Jun 2016
Anchoring and Agreement in Syntactic Annotations
Anchoring and Agreement in Syntactic Annotations
Yevgeni Berzak
Yan Huang
Andrei Barbu
Anna Korhonen
Boris Katz
75
5
0
15 May 2016
Dependency Parsing with LSTMs: An Empirical Evaluation
Dependency Parsing with LSTMs: An Empirical Evaluation
A. Kuncoro
Yu Sawai
Kevin Duh
Yuji Matsumoto
129
3
0
22 Apr 2016
Recursive Neural Conditional Random Fields for Aspect-based Sentiment
  Analysis
Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis
Wenya Wang
Sinno Jialin Pan
Daniel Dahlmeier
Xiaokui Xiao
285
386
0
22 Mar 2016
Stack-propagation: Improved Representation Learning for Syntax
Stack-propagation: Improved Representation Learning for Syntax
Yuan Zhang
David J. Weiss
162
87
0
21 Mar 2016
Globally Normalized Transition-Based Neural Networks
Globally Normalized Transition-Based Neural Networks
D. Andor
Chris Alberti
David J. Weiss
Aliaksei Severyn
Alessandro Presta
Kuzman Ganchev
Slav Petrov
Michael Collins
239
571
0
19 Mar 2016
Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature
  Representations
Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations
E. Kiperwasser
Yoav Goldberg
282
680
0
14 Mar 2016
Easy-First Dependency Parsing with Hierarchical Tree LSTMs
Easy-First Dependency Parsing with Hierarchical Tree LSTMs
E. Kiperwasser
Yoav Goldberg
326
66
0
01 Mar 2016
Mapping Unseen Words to Task-Trained Embedding Spaces
Mapping Unseen Words to Task-Trained Embedding Spaces
Pranava Swaroop Madhyastha
Joey Tianyi Zhou
Kevin Gimpel
Karen Livescu
SSL
118
15
0
08 Oct 2015
A Primer on Neural Network Models for Natural Language Processing
A Primer on Neural Network Models for Natural Language Processing
Yoav Goldberg
AI4CE
245
1,199
0
02 Oct 2015
Improved Transition-Based Parsing by Modeling Characters instead of
  Words with LSTMs
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMsConference on Empirical Methods in Natural Language Processing (EMNLP), 2015
Miguel Ballesteros
Chris Dyer
Noah A. Smith
216
299
0
04 Aug 2015
Leverage Financial News to Predict Stock Price Movements Using Word
  Embeddings and Deep Neural Networks
Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks
Yang Peng
Hui Jiang
AIFin
194
91
0
24 Jun 2015
A Bayesian Model for Generative Transition-based Dependency Parsing
A Bayesian Model for Generative Transition-based Dependency ParsingInternational Conference on Dependency Linguistics (Depling), 2015
Jan Buys
Phil Blunsom
99
10
0
13 Jun 2015
Transition-Based Dependency Parsing with Stack Long Short-Term Memory
Transition-Based Dependency Parsing with Stack Long Short-Term MemoryAnnual Meeting of the Association for Computational Linguistics (ACL), 2015
Chris Dyer
Miguel Ballesteros
Wang Ling
Austin Matthews
Noah A. Smith
230
814
0
29 May 2015
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