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Quantitative reasoning is a higher-order reasoning skill that any intelligent natural language understanding system can reasonably be expected to handle.
Hereditary and environmental components of quantitative reasoning
Richard E Stafford. 1972 · 1972
Earlier work this paper cites.
Manual for kit of factor-referenced cognitive tests , volume 102
Ruth B Ekstrom, Diran Dermen, and Harry Horace Harman. 1976 · 1976
Earlier work this paper cites.
Generalized quantifiers and natural language
Jon Barwise and Robin Cooper. 1981 · 1981
Earlier work this paper cites.
Using the framework
Robin Cooper, Dick Crouch, Jan Van Eijck, Chris Fox, Johan Van Genabith, Jan Jaspars, Hans Kamp, David Milward, Manfred Pinkal, Massimo Poesio, et al. 1996 · 1996
Earlier work this paper cites.
Pragmatics
Stephen C Levinson. 2001 · 2001
Earlier work this paper cites.
Entailment, intensionality and text understanding
Cleo Condoravdi, Dick Crouch, Valeria De Paiva, Reinhard Stolle, and Daniel G Bobrow. 2003 · 2003
Earlier work this paper cites.
Recognising textual entailment with logical inference
Johan Bos and Katja Markert. 2005 · 2005
Earlier work this paper cites.
Web based probabilistic textual entailment
Oren Glickman, Ido Dagan, and Moshe Koppel. 2005 · 2005
Earlier work this paper cites.
Robust textual inference via graph matching
Aria Haghighi, Andrew Ng, and Christopher Manning. 2005 · 2005
Earlier work this paper cites.
The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
Earlier work this paper cites.
Methods for using textual entailment in open-domain question answering
Sanda Harabagiu and Andrew Hickl. 2006 · 2006
Earlier work this paper cites.
Investigating a generic paraphrase-based approach for relation extraction
Lorenza Romano, Milen Kouylekov, Idan Szpektor, Ido Dagan, and Alberto Lavelli. 2006 · 2006
Earlier work this paper cites.
Learning textual entailment from examples
F Zanzotto, Alessandro Moschitti, Marco Pennacchiotti, and M Pazienza. 2006 · 2006
Earlier work this paper cites.
The third pascal recognizing textual entailment challenge
Danilo Giampiccolo, Bernardo Magnini, Ido Dagan, and Bill Dolan. 2007 · 2007
Earlier work this paper cites.
Learning textual entailment using svms and string similarity measures
Prodromos Malakasiotis and Ion Androutsopoulos. 2007 · 2007
Earlier work this paper cites.
Finding contradictions in text
Marie-Catherine De Marneffe, Anna N. Rafferty, and Christopher D. Manning. 2008 · 2008
Earlier work this paper cites.
Number as a cognitive technology: Evidence from pirahã language and cognition
Michael C Frank, Daniel L Everett, Evelina Fedorenko, and Edward Gibson. 2008 · 2008
Cited alongside, same era.
Multi-word expressions in textual inference: Much ado about nothing?
Marie-Catherine DeMarneffe, Sebastian Padó, and Christopher D Manning. 2009 · 2009
Cited alongside, same era.
Natural language inference
Bill MacCartney. 2009 · 2009
Cited alongside, same era.
Building textual entailment specialized data sets: a methodology for isolating linguistic phenomena relevant to inference
Luisa Bentivogli, Elena Cabrio, Ido Dagan, Danilo Giampiccolo, Medea Lo Leggio, and Bernardo Magnini. 2010 · 2010
Cited alongside, same era.
The fourth pascal recognizing textual entailment challenge
Ido Dagan, Bill Dolan, Bernardo Magnini, and Dan Roth. 2010 · 2010
Cited alongside, same era.
Ask not what textual entailment can do for you…
Learning from explicit and implicit supervision jointly for algebra word problems
Shyam Upadhyay, Ming-Wei Chang, Kai-Wei Chang, and Wen-tau Yih. 2016 · 2016
Later among the works it cites.
Refining raw sentence representations for textual entailment recognition via attention
Jorge Balazs, Edison Marrese-Taylor, Pablo Loyola, and Yutaka Matsuo. 2017 · 2017
Later among the works it cites.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
Later among the works it cites.
Learning fine-grained expressions to solve math word problems
Danqing Huang, Shuming Shi, Chin-Yew Lin, and Jian Yin. 2017 · 2017
Later among the works it cites.
Shortcut-stacked sentence encoders for multi-domain inference
Yixin Nie and Mohit Bansal. 2017 · 2017
Later among the works it cites.
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Mark Sammons, VG Vydiswaran, and Dan Roth. 2010 · 2010
Cited alongside, same era.
The number sense: How the mind creates mathematics
Stanislas Dehaene. 2011 · 2011
Cited alongside, same era.
Naturalli: Natural logic inference for common sense reasoning
Gabor Angeli and Christopher D Manning. 2014 · 2014
Cited alongside, same era.
Learning to solve arithmetic word problems with verb categorization
Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, and Nate Kushman. 2014 · 2014
Cited alongside, same era.
A sick cure for the evaluation of compositional distributional semantic models
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, Roberto Zamparelli, et al. 2014 · 2014
Cited alongside, same era.
A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Cited alongside, same era.
Subhro Roy. 2017 · 2017
Later among the works it cites.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel R Bowman. 2017 · 2017
Later among the works it cites.
What knowledge is needed to solve the rte5 textual entailment challenge?
Peter Clark. 2018 · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Breaking nli systems with sentences that require simple lexical inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018 · 2018
Later among the works it cites.
Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R Bowman, and Noah A Smith. 2018 · 2018
Later among the works it cites.
Scitail: A textual entailment dataset from science question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
Later among the works it cites.
Advances in pre-training distributed word representations
Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin. 2018 · 2018
Later among the works it cites.
Stress test evaluation for natural language inference
Aakanksha Naik, Abhilasha Ravichander, Norman Sadeh, Carolyn Rose, and Graham Neubig. 2018 · 2018
Later among the works it cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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