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Large-scale sequence-to-sequence models have shown to be adept at both multiple-choice and open-domain commonsense reasoning tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2019 · 1904
Earlier work this paper cites.
The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability
Joseph L Fleiss and Jacob Cohen. 1973 · 1973
Earlier work this paper cites.
Preference semantics, iii-formedness, and metaphor
Dan Fass and Yorick Wilks. 1983 · 1983
Earlier work this paper cites.
Automatically generating extraction patterns from untagged text
E. Riloff. 1996 · 1996
Earlier work this paper cites.
Template-based information extraction from tree-structured html documents
S. Yih. 1997 · 1997
Earlier work this paper cites.
Extracting patterns and relations from the world wide web
S. Brin. 1998 · 1998
Earlier work this paper cites.
Extracting relations from large plain-text collections
Eugene Agichtein and L. Gravano. 1999 · 1999
Earlier work this paper cites.
Learning to construct knowledge bases from the world wide web
M. Craven, Dan DiPasquo, Dayne Freitag, A. McCallum, Tom Michael Mitchell, K. Nigam, and Seán Slattery. 2000 · 2000
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Unsupervised commonsense question answering with self-talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2004
Earlier work this paper cites.
Yago: A core of semantic knowledge
Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007 · 2007
Earlier work this paper cites.
DBpedia: A multilingual cross-domain knowledge base
Pablo Mendes, Max Jakob, and Christian Bizer. 2012 · 2012
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Rule-based information extraction is dead! long live rule-based information extraction systems!
Laura Chiticariu, Yunyao Li, and Frederick R. Reiss. 2013 · 2013
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Conceptnet 5: A large semantic network for relational knowledge
Robyn Speer and Catherine Havasi. 2013 · 2013
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Nutrition interventions at point-of-sale to encourage healthier food purchasing: a systematic review
Selma Coelho Liberato, Ross Stewart Bailie, and Julie K. Brimblecombe. 2014 · 2014
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Ms marco: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng. 2016 · 2016
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Addressing challenges in promoting healthy lifestyles: the al-chatbot approach
Ahmed Fadhil and Silvia Gabrielli. 2017 · 2017
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Application of synchronous text-based dialogue systems in mental health interventions: Systematic review
Simon Hoermann, Kathryn L. McCabe, David N. Milne, and Rafael Alejandro Calvo. 2017 · 2017
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MaskGAN: Better text generation via filling in the _____
William Fedus, Ian Goodfellow, and Andrew M. Dai. 2018 · 2018
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Conversational agents in healthcare: a systematic review
Liliana Laranjo, Adam G. Dunn, Huong Ly Tong, Ahmet Baki Kocaballi, Jessica A. Chen, Rabia Bashir, Didi Surian, Blanca Gallego, Farah Magrabi, Annie Y. S. Lau, and Enrico W. Coiera. 2018 · 2018
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How context affects language models’ factual predictions
Fabio Petroni, Patrick Lewis, Aleksandra Piktus, Tim Rocktäschel, Yuxiang Wu, Alexander H. Miller, and Sebastian Riedel. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Beyond accuracy: Behavioral testing of NLP models with CheckList
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
Later among the works it cites.
Extraction of explicit and implicit cause-effect relationships in patient-reported diabetes-related tweets from 2017 to 2021: Deep learning approach
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Never-ending learning
T. Mitchell, W. Cohen, E. Hruschka, P. Talukdar, B. Yang, J. Betteridge, A. Carlson, B. Dalvi, M. Gardner, B. Kisiel, J. Krishnamurthy, N. Lao, K. Mazaitis, T. Mohamed, N. Nakashole, E. Platanios, A. Ritter, M. Samadi, B. Settles, R. Wang, D. Wijaya, A. Gupta, X. Chen, A. Saparov, M. Greaves, and J. Welling. 2018 · 2018
Cited alongside, same era.
Reasoning about actions and state changes by injecting commonsense knowledge
Niket Tandon, Bhavana Dalvi, Joel Grus, Wen-tau Yih, Antoine Bosselut, and Peter Clark. 2018 · 2018
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Comet: Commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Çelikyilmaz, and Yejin Choi. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Atomic: An atlas of machine commonsense for if-then reasoning
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith, and Yejin Choi. 2019 · 2019
Cited alongside, same era.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
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Effectiveness and safety of using chatbots to improve mental health: Systematic review and meta-analysis
Alaa A. Abd-alrazaq, Asma Rababeh, Mohannad Alajlani, Bridgette M. Bewick, and Mowafa Said Househ. 2020 · 2020
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Adrian Ahne, Vivek Khetan, Xavier Tannier, Md Imbesat Hassan Rizvi, Thomas Czernichow, Francisco Orchard, Charline Bour, Andy E. Fano, and Guy Fagherazzi. 2022 · 2021
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Dynamic neuro-symbolic knowledge graph construction for zero-shot commonsense question answering
Antoine Bosselut, Ronan Le Bras, and Yejin Choi. 2021 · 2021
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Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, Zhengnan Xie, Hannah Smith, Leighanna Pipatanangkura, and Peter Clark. 2021 · 2021
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Social marketing-based interventions to promote healthy nutrition behaviors: a systematic review protocol
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Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2021 · 2021
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How many data points is a prompt worth?
Teven Le Scao and Alexander Rush. 2021 · 2021
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Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, and Rodrigo Nogueira. 2021b · 2021
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Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics
Artidoro Pagnoni, Vidhisha Balachandran, and Yulia Tsvetkov. 2021 · 2021
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Teach me to explain: A review of datasets for explainable natural language processing
Sarah Wiegreffe and Ana Marasović. 2021 · 2021
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MIMICause: Representation and automatic extraction of causal relation types from clinical notes
Vivek Khetan, Md Imbesat Rizvi, Jessica Huber, Paige Bartusiak, Bogdan Sacaleanu, and Andrew Fano. 2022 · 2022
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022 · 2022
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The unreliability of explanations in few-shot in-context learning
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