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Counterfactual reasoning requires predicting how alternative events, contrary to what actually happened, might have resulted in different outcomes.
BERTScore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
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Probing neural network comprehension of natural language arguments
Timothy Niven and Hung-Yu Kao. 2019 · 1907
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The problem of counterfactual conditionals
Nelson Goodman. 1947 · 1947
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Causality: models, reasoning and inference , volume 29
Judea Pearl. 2000 · 2000
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Mental models and counterfactual thoughts about what might have been
Ruth MJ Byrne. 2002 · 2002
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BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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What is a mechanism? a counterfactual account
Jim Woodward. 2002 · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Toward a useful concept of causality for lexical semantics
Jerry R Hobbs. 2005 · 2005
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The functional theory of counterfactual thinking
Kai Epstude and Neal J Roese. 2008 · 2008
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Semeval-2012 task 7: Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Melissa Roemmele, Cosmin Adrian Bejan, and Andrew S. Gordon. 2011 · 2012
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Counterfactual reasoning and learning systems: The example of computational advertising
Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X Charles, D Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, and Ed Snelson. 2013 · 2013
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Event schema induction with a probabilistic entity-driven model
Nathanael Chambers. 2013 · 2013
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
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Statistical script learning with multi-argument events
Karl Pichotta and Raymond Mooney. 2014 · 2014
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Evaluating machine translation for assimilation via a gap-filling task
Ekaterina Ageeva, Mikel L Forcada, Francis M Tyers, and Juan Antonio Pérez-Ortiz. 2015 · 2015
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From word embeddings to document distances
Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, and Kilian Q. Weinberger. 2015 · 2015
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan R. Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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A theme-rewriting approach for generating algebra word problems
Challenges in data-to-document generation
Sam Wiseman, Stuart M. Shieber, and Alexander M. Rush. 2017 · 2017
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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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Improving a neural semantic parser by counterfactual learning from human bandit feedback
Carolin Lawrence and Stefan Riezler. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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Swag: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
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Rik Koncel-Kedziorski, Ioannis Konstas, Luke S. Zettlemoyer, and Hannaneh Hajishirzi. 2016 · 2016
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How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
Chia-Wei Liu, Ryan Lowe, Iulian Serban, Michael Noseworthy, Laurent Charlin, and Joelle Pineau. 2016 · 2016
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A corpus and evaluation framework for deeper understanding of commonsense stories
Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, and James Allen. 2016 · 2016
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Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
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Re-evaluating automatic metrics for image captioning
Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis, and Erkut Erdem. 2017 · 2017
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Ryan Lowe, Michael Noseworthy, Iulian Serban, Nicolas Angelard-Gontier, Yoshua Bengio, and Joelle Pineau. 2017 · 2017
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Style transfer from non-parallel text by cross-alignment
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Texar: A modularized, versatile, and extensible toolkit for text generation
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