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Existing datasets for natural language inference (NLI) have propelled research on language understanding.
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K. S. Jones. 1993 · 1993
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Motivations and methods for text simplification
R. Chandrasekar, C. Doran, and B. Srinivas. 1996 · 1996
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Long short-term memory
S. Hochreiter and J. Schmidhuber. 1997 · 1997
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Discovery of inference rules for question-answering
D. Lin and P. Pantel. 2001 · 2001
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Paraphrasing with bilingual parallel corpora
C. Bannard and C. Callison-Burch. 2005 · 2005
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The PASCAL recognising textual entailment challenge
I. Dagan, O. Glickman, and B. Magnini. 2006 · 2006
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The question generation shared task and evaluation challenge
V. Rus and C. G. Arthur. 2009 · 2009
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Sequence transduction with recurrent neural networks
A. Graves. 2012 · 2012
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Mctest: A challenge dataset for the open-domain machine comprehension of text
M. Richardson, C. J. Burges, and E. Renshaw. 2013 · 2013
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Adam: A method for stochastic optimization
D. Kingma and J. Ba. 2014 · 2014
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A SICK cure for the evaluation of compositional distributional semantic models
M. Marelli, S. Menini, M. Baroni, L. Bentivogli, R. bernardi, and R. Zamparelli. 2014 · 2014
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Glove: Global vectors for word representation
J. Pennington, R. Socher, and C. D. Manning. 2014 · 2014
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Neural machine translation by jointly learning to align and translate
D. Bahdanau, K. Cho, and Y. Bengio. 2015 · 2015
Cited alongside, same era.
A large annotated corpus for learning natural language inference
S. Bowman, G. Angeli, C. Potts, and C. D. Manning. 2015 · 2015
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Question-answer driven semantic role labeling: Using natural language to annotate natural language
L. He, M. Lewis, and L. Zettlemoyer. 2015 · 2015
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Incorporating copying mechanism in sequence-to-sequence learning
J. Gu, Z. Lu, H. Li, and V. O. Li. 2016 · 2016
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Generating natural language inference chains
V. Kolesnyk, T. Rocktäschel, and S. Riedel. 2016 · 2016
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Learning to parse and translate improves neural machine translation
A. Eriguchi, Y. Tsuruoka, and K. Cho. 2017 · 2017
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Convolutional sequence to sequence learning
J. Gehring, M. Auli, D. Grangier, D. Yarats, and Y. N. Dauphin. 2017 · 2017
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
M. Joshi, E. Choi, D. Weld, and L. Zettlemoyer. 2017 · 2017
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NewsQA: A machine comprehension dataset
A. Trischler, T. Wang, X. Yuan, J. Harris, A. Sordoni, P. Bachman, and K. Suleman. 2017 · 2017
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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin. 2017 · 2017
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E. Pavlick and C. Callison-Burch. 2016 · 2016
Cited alongside, same era.
SQuAD: 100,000+ questions for machine comprehension of text
P. Rajpurkar, J. Zhang, K. Lopyrev, and P. Liang. 2016 · 2016
Cited alongside, same era.
Movieqa: Understanding stories in movies through question-answering
M. Tapaswi, Y. Zhu, R. Stiefelhagen, A. Torralba, R. Urtasun, and S. Fidler. 2016 · 2016
Cited alongside, same era.
Online segment to segment neural transduction
L. Yu, J. Buys, and P. Blunsom. 2016 · 2016
Cited alongside, same era.
Improved neural machine translation with a syntax-aware encoder and decoder
H. Chen, S. Huang, D. Chiang, and J. Chen. 2017 · 2017
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
A. Conneau, D. Kiela, H. Schwenk, L. Barrault, and A. Bordes. 2017 · 2017
Cited alongside, same era.
Stanford’s graph-based neural dependency parser at the conll 2017 shared task
T. Dozat, P. Qi, and C. D. Manning. 2017 · 2017
Cited alongside, same era.
Later among the works it cites.
Inference is everything: Recasting semantic resources into a unified evaluation framework
Aaron Steven White, Pushpendre Rastogi, Kevin Duh, and Benjamin Van Durme. 2017 · 2017
Later among the works it cites.
A broad-coverage challenge corpus for sentence understanding through inference
A. Williams, N. Nangia, and S. R. Bowman. 2017 · 2017
Later among the works it cites.
Annotation artifacts in natural language inference data
S. Gururangan, S. Swayamdipta, O. Levy, R. Schwartz, S. R. Bowman, and N. A. Smith. 2018 · 2018
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Scitail: A textual entailment dataset from science question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
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Crowdsourcing question–answer meaning representations
J. Michael, G. Stanovsky, L. He, I. Dagan, and L. Zettlemoyer. 2018 · 2018
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Towards a unified natural language inference framework to evaluate sentence representations
Adam Poliak, Aparajita Haldar, Rachel Rudinger, J Edward Hu, Ellie Pavlick, Aaron Steven White, and Benjamin Van Durme. 2018 · 2018
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Know what you don’t know: Unanswerable questions for SQuAD
P. Rajpurkar, R. Jia, and P. Liang. 2018 · 2018
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