Fetching the paper…
Reading the bibliography…
This paper presents a novel neural machine translation model which jointly learns translation and source-side latent graph representations of sentences.
Computer-Intensive Methods for Testing Hypotheses: An Introduction
Eric W. Noreen. 1989 · 1989
Earlier work this paper cites.
Efficient Normal-Form Parsing for Combinatory Categorial Grammar
Jason Eisner. 1996 · 1996
Earlier work this paper cites.
Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora
Dekai Wu. 1997 · 1997
Earlier work this paper cites.
A Syntax-based Statistical Translation Model
Kenji Yamada and Kevin Knight. 2001 · 2001
Earlier work this paper cites.
BLEU: A Method for Automatic Evaluation of Machine Translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Framewise Phoneme Classification with Bidirectional LSTM and Other Neural Network Architectures
Alex Graves and Jurgen Schmidhuber. 2005 · 2005
Earlier work this paper cites.
Online Large-Margin Training of Dependency Parsers
Ryan McDonald, Koby Crammer, and Fernando Pereira. 2005 · 2005
Earlier work this paper cites.
Feature Forest Models for Probabilistic HPSG Parsing
Yusuke Miyao and Jun’ichi Tsujii. 2008 · 2008
Earlier work this paper cites.
Automatic Evaluation of Translation Quality for Distant Language Pairs
Hideki Isozaki, Tsutomu Hirao, Kevin Duh, Katsuhito Sudoh, and Hajime Tsukada. 2010 · 2010
Earlier work this paper cites.
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, and Christopher D. Manning. 2011 · 2011
Earlier work this paper cites.
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2012 · 2012
Earlier work this paper cites.
Simple Customization of Recursive Neural Networks for Semantic Relation Classification
Kazuma Hashimoto, Makoto Miwa, Yoshimasa Tsuruoka, and Takashi Chikayama. 2013 · 2013
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.
On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
On the Elements of an Accurate Tree-to-String Machine Translation System
Graham Neubig and Kevin Duh. 2014 · 2014
Earlier work this paper cites.
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Cited alongside, same era.
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
Montreal Neural Machine Translation Systems for WMTf15
Sébastien Jean, Orhan Firat, Kyunghyun Cho, Roland Memisevic, and Yoshua Bengio. 2015 · 2015
Cited alongside, same era.
An Empirical Exploration of Recurrent Network Architectures
Rafal Jozefowicz, Wojciech Zaremba, and Ilya Sutskever. 2015 · 2015
Cited alongside, same era.
NAVER Machine Translation System for WAT 2015
Hyoung-Gyu Lee, JaeSong Lee, Jun-Seok Kim, and Chang-Ki Lee. 2015 · 2015
Cited alongside, same era.
When Are Tree Structures Necessary for Deep Learning of Representations?
Jiwei Li, Thang Luong, Dan Jurafsky, and Eduard Hovy. 2015 · 2015
Syntactically Guided Neural Machine Translation
Felix Stahlberg, Eva Hasler, Aurelien Waite, and Bill Byrne. 2016 · 2016
Later among the works it cites.
Charagram: Embedding Words and Sentences via Character n-grams
John Wieting, Mohit Bansal, Kevin Gimpel, and Karen Livescu. 2016 · 2016
Later among the works it cites.
Simple, Fast Noise-Contrastive Estimation for Large RNN Vocabularies
Barret Zoph, Ashish Vaswani, Jonathan May, and Kevin Knight. 2016 · 2016
Later among the works it cites.
Graph Convolutional Encoders for Syntax-aware Neural Machine Translation
Joost Bastings, Ivan Titov, Wilker Aziz, Diego Marcheggiani, and Khalil Sima’an. 2017 · 2017
Closest in time.
Enriching Word Vectors with Subword Information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
Closest in time.
Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder
Huadong Chen, Shujian Huang, David Chiang, and Jiajun Chen. 2017 · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015
Graham Neubig, Makoto Morishita, and Satoshi Nakamura. 2015 · 2015
Cited alongside, same era.
Evaluating Neural Machine Translation in English-Japanese Task
Zhongyuan Zhu. 2015 · 2015
Cited alongside, same era.
Kyoto University Participation to WAT 2016
Fabien Cromieres, Chenhui Chu, Toshiaki Nakazawa, and Sadao Kurohashi. 2016 · 2016
Cited alongside, same era.
Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation
Kazuma Hashimoto, Akiko Eriguchi, and Yoshimasa Tsuruoka. 2016 · 2016
Cited alongside, same era.
Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling
Hakan Inan, Khashayar Khosravi, and Richard Socher. 2016 · 2016
Cited alongside, same era.
Closest in time.
Deep Biaffine Attention for Neural Dependency Parsing
Timothy Dozat and Christopher D. Manning. 2017 · 2017
Closest in time.
Learning to Parse and Translate Improves Neural Machine Translation
Akiko Eriguchi, Yoshimasa Tsuruoka, and Kyunghyun Cho. 2017 · 2017
Closest in time.
A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, and Richard Socher. 2017 · 2017
Closest in time.
Deep Biaffine Attention for Neural Dependency Parsing
Yoon Kim, Carl Denton, Luong Hoang, and Alexander M. Rush. 2017 · 2017
Closest in time.
Modeling Source Syntax for Neural Machine Translation
Junhui Li, Deyi Xiong, Zhaopeng Tu, Muhua Zhu, Min Zhang, and Guodong Zhou. 2017 · 2017
Closest in time.
Using the Output Embedding to Improve Language Models
Ofir Press and Lior Wolf. 2017 · 2017
Closest in time.
Towards Bidirectional Hierarchical Representations for Attention-Based Neural Machine Translation
Baosong Yang, Derek F. Wong, Tong Xiao, Lidia S. Chao, and Jingbo Zhu. 2017 · 2017
Closest in time.
Learning to Compose Words into Sentences with Reinforcement Learning
Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, and Wang Ling. 2017 · 2017
Closest in time.
Dependency Parsing as Head Selection
Xingxing Zhang, Jianpeng Cheng, and Mirella Lapata. 2017 · 2017
Closest in time.