Fetching the paper…
Reading the bibliography…
Contextualized representation models such as ELMo (Peters et al., 2018a) and BERT (Devlin et al., 2018) have recently achieved state-of-the-art results on a diverse array of downstream NLP tasks.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
The necessity of parsing for predicate argument recognition
Daniel Gildea and Martha Palmer · 2002
Earlier work this paper cites.
The importance of syntactic parsing and inference in semantic role labeling
Vasin Punyakanok, Dan Roth, and Wen-tau Yih · 2008
Earlier work this paper cites.
SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals
Iris Hendrickx, Su Nam Kim, Zornitsa Kozareva, Preslav Nakov, Diarmuid Ó Séaghdha, Sebastian Padó, Marco Pennacchiotti, Lorenza Romano, and Stan Szpakowicz · 2009
Earlier work this paper cites.
The winograd schema challenge
Hector J. Levesque, Ernest Davis, and Leora Morgenstern · 2012
Earlier work this paper cites.
Resolving complex cases of definite pronouns: The Winograd schema challenge
Altaf Rahman and Vincent Ng · 2012
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S. Corrado, and Jeff Dean · 2013
Earlier work this paper cites.
OntoNotes release 5.0 LDC2013T19
Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, et al · 2013
Earlier work this paper cites.
One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson · 2014
Earlier work this paper cites.
GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
Earlier work this paper cites.
A gold standard dependency corpus for English
Natalia Silveira, Timothy Dozat, Marie-Catherine de Marneffe, Samuel Bowman, Miriam Connor, John Bauer, and Christopher D. Manning · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R. Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2015
Earlier work this paper cites.
Assessing the ability of LSTMs to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg · 2016
Earlier work this paper cites.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch · 2016
Earlier work this paper cites.
Does string-based neural MT learn source syntax?
Xing Shi, Inkit Padhi, and Kevin Knight · 2016
Cited alongside, same era.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al · 2016
Cited alongside, same era.
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg · 2017
Cited alongside, same era.
Proceedings of the Second Conference on Machine Translation
Ondřej Bojar, Christian Buck, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, and Julia Kreutzer (eds.) · 2017
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes · 2017
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Later among the works it cites.
Assessing composition in sentence vector representations
Allyson Ettinger, Ahmed Elgohary, Colin Phillips, and Philip Resnik · 2018
Later among the works it cites.
AllenNLP: A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer · 2018
Later among the works it cites.
Colorless green recurrent networks dream hierarchically
Kristina Gulordava, Piotr Bojanowski, Edouard Grave, Tal Linzen, and Marco Baroni · 2018
Later among the works it cites.
Jointly predicting predicates and arguments in neural semantic role labeling
Luheng He, Kenton Lee, Omer Levy, and Luke Zettlemoyer · 2018
Later among the works it cites.
Universal language model fine-tuning for text classification
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
End-to-end neural coreference resolution
Kenton Lee, Luheng He, Mike Lewis, and Luke Zettlemoyer · 2017
Cited alongside, same era.
Learned in translation: Contextualized word vectors
Bryan McCann, James Bradbury, Caiming Xiong, and Richard Socher · 2017
Cited alongside, same era.
Automatic differentiation in PyTorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
Cited alongside, same era.
Semantic proto-role labeling
Adam Teichert, Adam Poliak, Benjamin Van Durme, and Matthew Gormley · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Inference is everything: Recasting semantic resources into a unified evaluation framework
Aaron Steven White, Pushpendre Rastogi, Kevin Duh, and Benjamin Van Durme · 2017
Cited alongside, same era.
On internal language representations in deep learning: An analysis of machine translation and speech recognition
Yonatan Belinkov · 2018
Cited alongside, same era.
Jeremy Howard and Sebastian Ruder · 2018
Later among the works it cites.
Constituency parsing with a self-attentive encoder
Nikita Kitaev and Dan Klein · 2018
Later among the works it cites.
LSTMs can learn syntax-sensitive dependencies well, but modeling structure makes them better
Adhiguna Kuncoro, Chris Dyer, John Hale, Dani Yogatama, Stephen Clark, and Phil Blunsom · 2018
Later among the works it cites.
Higher-order coreference resolution with coarse-to-fine inference
Kenton Lee, Luheng He, and Luke Zettlemoyer · 2018
Later among the works it cites.
Targeted syntactic evaluation of language models
Rebecca Marvin and Tal Linzen · 2018
Later among the works it cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
Later among the works it cites.
Neural Davidsonian semantic proto-role labeling
Rachel Rudinger, Adam Teichert, Ryan Culkin, Sheng Zhang, and Benjamin Van Durme · 2018
Later among the works it cites.
Linguistically-informed self-attention for semantic role labeling
Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, and Andrew McCallum · 2018
Later among the works it cites.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman · 2018
Later among the works it cites.
Language modeling teaches you more than translation does: Lessons learned through auxiliary syntactic task analysis
Kelly Zhang and Samuel Bowman · 2018
Later among the works it cites.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler · 2018
Later among the works it cites.