Fetching the paper…
Reading the bibliography…
Most modern Information Extraction (IE) systems are implemented as sequential taggers and only model local dependencies.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
John D Lafferty, Andrew McCallum, and Fernando CN Pereira. 2001 · 2001
Earlier work this paper cites.
Introduction to the conll-2003 shared task: Language-independent named entity recognition
Kim Sang Tjong, F Erik, and Fien De Meulder. 2003 · 2003
Earlier work this paper cites.
Incorporating non-local information into information extraction systems by gibbs sampling
Jenny Rose Finkel, Trond Grenager, and Christopher Manning. 2005 · 2005
Earlier work this paper cites.
Visual information extraction
Yonatan Aumann, Ronen Feldman, Yair Liberzon, Benjamin Rosenfeld, and Jonathan Schler. 2006 · 2006
Earlier work this paper cites.
Extracting clinical relationships from patient narratives
Angus Roberts, Robert Gaizauskas, and Mark Hepple. 2008 · 2008
Earlier work this paper cites.
Distant supervision for relation extraction without labeled data
Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. 2009 · 2009
Earlier work this paper cites.
Generalized expectation criteria for semi-supervised learning with weakly labeled data
Gideon S Mann and Andrew McCallum. 2010 · 2010
Earlier work this paper cites.
You are who you know: inferring user profiles in online social networks
Alan Mislove, Bimal Viswanath, Krishna P Gummadi, and Peter Druschel. 2010 · 2010
Earlier work this paper cites.
Event discovery in social media feeds
Edward Benson, Aria Haghighi, and Regina Barzilay. 2011 · 2011
Earlier work this paper cites.
Extracting relations within and across sentences
Kumutha Swampillai and Mark Stevenson. 2011 · 2011
Earlier work this paper cites.
Learning to discover social circles in ego networks
Jure Leskovec and Julian J Mcauley. 2012 · 2012
Cited alongside, same era.
Multi event extraction guided by global constraints
Roi Reichart and Regina Barzilay. 2012 · 2012
Cited alongside, same era.
Joint event extraction via structured prediction with global features
Qi Li, Heng Ji, and Liang Huang. 2013 · 2013
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Cited alongside, same era.
Weakly supervised user profile extraction from twitter
Jiwei Li, Alan Ritter, and Eduard Hovy. 2014 · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
Later among the works it cites.
End-to-end sequence labeling via bi-directional lstm-cnns-crf
Xuezhe Ma and Eduard Hovy. 2016 · 2016
Later among the works it cites.
End-to-end relation extraction using lstms on sequences and tree structures
Makoto Miwa and Mohit Bansal. 2016 · 2016
Later among the works it cites.
Cross-sentence n-ary relation extraction with graph lstms
Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova, and 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.
Bert: Pre-training of deep bidirectional transformers for language understanding
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Chemdner: The drugs and chemical names extraction challenge
Martin Krallinger, Florian Leitner, Obdulia Rabal, Miguel Vazquez, Julen Oyarzabal, and Alfonso Valencia. 2015 · 2015
Cited alongside, same era.
Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D Manning. 2015 · 2015
Cited alongside, same era.
Harnessing deep neural networks with logic rules
Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, and Eric Xing. 2016 · 2016
Cited alongside, same era.
Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M Rush. 2016 · 2016
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling. 2016 · 2016
Cited alongside, same era.
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Closest in time.
Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Closest in time.
Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2018 · 2018
Closest in time.
N-ary relation extraction using graph-state lstm
Linfeng Song, Yue Zhang, Zhiguo Wang, and Daniel Gildea. 2018 · 2018
Closest in time.
Hybrid semi-markov crf for neural sequence labeling
Zhixiu Ye and Zhen-Hua Ling. 2018 · 2018
Closest in time.
Graph convolution over pruned dependency trees improves relation extraction
Yuhao Zhang, Peng Qi, and Christopher D Manning. 2018 · 2018
Closest in time.