Fetching the paper…
Reading the bibliography…
Deep learning has emerged as a versatile tool for a wide range of NLP tasks, due to its superior capacity in representation learning.
Knowledge-based artificial neural networks
Geoffrey G Towell and Jude W Shavlik. 1994 · 1994
Earlier work this paper cites.
Dual decomposition in stochastic integer programming
Claus C CarøE and Rüdiger Schultz. 1999 · 1999
Earlier work this paper cites.
Constructing biological knowledge bases by extracting information from text sources
Mark Craven and Johan Kumlien. 1999 · 1999
Earlier work this paper cites.
Loopy belief propagation for approximate inference: An empirical study
Kevin P Murphy, Yair Weiss, and Michael I Jordan. 1999 · 1999
Earlier work this paper cites.
A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003 · 2003
Earlier work this paper cites.
Part-of-speech tagging using virtual evidence and negative training
Sheila M Reynolds and Jeff A Bilmes. 2005 · 2005
Earlier work this paper cites.
Generating typed dependency parses from phrase structure parses
Marie-Catherine de Marneffe, Bill MacCartney, and Christopher D. Manning. 2006 · 2006
Earlier work this paper cites.
Markov logic networks
Matthew Richardson and Pedro Domingos. 2006 · 2006
Earlier work this paper cites.
Guiding semi-supervision with constraint-driven learning
Ming-Wei Chang, Lev Ratinov, and Dan Roth. 2007 · 2007
Earlier work this paper cites.
Joint inference in information extraction
Hoifung Poon and Pedro Domingos. 2007 · 2007
Earlier work this paper cites.
Virtual evidence for training speech recognizers using partially labeled data
Amarnag Subramanya and Jeff Bilmes. 2007 · 2007
Earlier work this paper cites.
Learning from labeled features using generalized expectation criteria
Gregory Druck, Gideon Mann, and Andrew McCallum. 2008 · 2008
Earlier work this paper cites.
Generalized expectation criteria for semi-supervised learning of conditional random fields
Gideon S Mann and Andrew McCallum. 2008 · 2008
Earlier work this paper cites.
Overview of biocreative ii gene normalization
Alexander A Morgan, Zhiyong Lu, Xinglong Wang, Aaron M Cohen, Juliane Fluck, Patrick Ruch, Anna Divoli, Katrin Fundel, Robert Leaman, Jörg Hakenberg, et al. 2008 · 2008
Earlier work this paper cites.
Joint unsupervised coreference resolution with markov logic
Hoifung Poon and Pedro Domingos. 2008 · 2008
Earlier work this paper cites.
Overview of bionlp’09 shared task on event extraction
Jin-Dong Kim, Tomoko Ohta, Sampo Pyysalo, Yoshinobu Kano, and Jun’ichi Tsujii. 2009 · 2009
Earlier work this paper cites.
On the use of virtual evidence in conditional random fields
Xiao Li. 2009 · 2009
Cited alongside, same era.
Distant supervision for relation extraction without labeled data
Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. 2009 · 2009
Cited alongside, same era.
Joint inference for knowledge extraction from biomedical literature
Hoifung Poon and Lucy Vanderwende. 2010 · 2010
Cited alongside, same era.
Knowledge-based weak supervision for information extraction of overlapping relations
Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke Zettlemoyer, and Daniel S Weld. 2011 · 2011
Cited alongside, same era.
A short introduction to probabilistic soft logic
Angelika Kimmig, Stephen Bach, Matthias Broecheler, Bert Huang, and Lise Getoor. 2012 · 2012
Cited alongside, same era.
MSR SPLAT, a language analysis toolkit
Chris Quirk, Pallavi Choudhury, Jianfeng Gao, Hisami Suzuki, Kristina Toutanova, Michael Gamon, Wen-tau Yih, and Lucy Vanderwende. 2012 · 2012
Leveraging deep neural networks and knowledge graphs for entity disambiguation
Hongzhao Huang, Larry Heck, and Heng Ji. 2015 · 2015
Later among the works it cites.
Grounded semantic parsing for complex knowledge extraction
Ankur P Parikh, Hoifung Poon, and Kristina Toutanova. 2015 · 2015
Later among the works it cites.
Gnormplus: an integrative approach for tagging genes, gene families, and protein domains
Chih-Hsuan Wei, Hung-Yu Kao, and Zhiyong Lu. 2015 · 2015
Later among the works it cites.
Improving coreference resolution by learning entity-level distributed representations
Kevin Clark and Christopher D Manning. 2016 · 2016
Later among the works it cites.
Deep learning , volume 1
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio. 2016 · 2016
Later among the works it cites.
Harnessing deep neural networks with logic rules
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
Cited alongside, same era.
Distributional semantics resources for biomedical text processing
S. Pyysalo, F. Ginter, H. Moen, T. Salakoski, and S. Ananiadou. 2013 · 2013
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Semi-supervised learning with deep generative models
Diederik P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling. 2014 · 2014
Cited alongside, same era.
The Stanford CoreNLP natural language processing toolkit
Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014 · 2014
Cited alongside, same era.
Probabilistic reasoning in intelligent systems: networks of plausible inference
Judea Pearl. 2014 · 2014
Cited alongside, same era.
Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, and Eric Xing. 2016a · 2016
Later among the works it cites.
Deep neural networks with massive learned knowledge
Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, and Eric Xing. 2016b · 2016
Later among the works it cites.
Composing graphical models with neural networks for structured representations and fast inference
Matthew Johnson, David K Duvenaud, Alex Wiltschko, Ryan P Adams, and Sandeep R Datta. 2016 · 2016
Later among the works it cites.
Neural relation extraction with selective attention over instances
Yankai Lin, Shiqi Shen, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. 2016 · 2016
Later among the works it cites.
Data programming: Creating large training sets, quickly
Alexander J Ratner, Christopher M De Sa, Sen Wu, Daniel Selsam, and Christopher Ré. 2016 · 2016
Later among the works it cites.
Learning the structure of generative models without labeled data
Stephen H Bach, Bryan He, Alexander Ratner, and Christopher Ré. 2017 · 2017
Later among the works it cites.
Identifying civilians killed by police with distantly supervised entity-event extraction
Katherine Keith, Abram Handler, Michael Pinkham, Cara Magliozzi, Joshua McDuffie, and Brendan O’Connor. 2017 · 2017
Later among the works it cites.
Heterogeneous supervision for relation extraction: A representation learning approach
Liyuan Liu, Xiang Ren, Qi Zhu, Shi Zhi, Huan Gui, Heng Ji, and Jiawei Han. 2017 · 2017
Later among the works it cites.
Cross-sentence n-ary relation extraction with graph lstms
Nanyun Peng, Hoifung Poon, Chris Quirk, and Kristina Toutanova Wen tau Yih. 2017 · 2017
Later among the works it cites.
Distant supervision for relation extraction beyond the sentence boundary
Chris Quirk and Hoifung Poon. 2017 · 2017
Later among the works it cites.
Posterior regularization for structured latent variable models
Kuzman Ganchev, Jennifer Gillenwater, Ben Taskar, et al. 2010 · 2049
Closest in time.