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Existing commonsense reasoning datasets for AI and NLP tasks fail to address an important aspect of human life: cultural differences.
Social bias frames: Reasoning about social and power implications of language
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Graphviz and dynagraph—static and dynamic graph drawing tools
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ConceptNet—a practical commonsense reasoning tool-kit
Liu, H.; and Singh, P. 2004 · 2004
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Conceptnet 5
Speer, R.; and Havasi, C. 2012 · 2012
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Mctest: A challenge dataset for the open-domain machine comprehension of text
Richardson, M.; Burges, C. J.; and Renshaw, E. 2013 · 2013
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Commonsense reasoning and commonsense knowledge in artificial intelligence
Davis, E.; and Marcus, G. 2015 · 2015
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Squad: 100,000+ questions for machine comprehension of text
Rajpurkar, P.; Zhang, J.; Lopyrev, K.; and Liang, P. 2016 · 2016
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Conceptnet 5.5: An open multilingual graph of general knowledge
Speer, R.; Chin, J.; and Havasi, C. 2016 · 2016
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Searchqa: A new q&a dataset augmented with context from a search engine
Mitre at semeval-2018 task 11: Commonsense reasoning without commonsense knowledge
Merkhofer, E.; Henderson, J.; Bloom, D.; Strickhart, L.; and Zarrella, G. 2018 · 2018
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Event2mind: Commonsense inference on events, intents, and reactions
Rashkin, H.; Sap, M.; Allaway, E.; Smith, N. A.; and Choi, Y. 2018 · 2018
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CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
Talmor, A.; Herzig, J.; Lourie, N.; and Berant, J. 2018 · 2018
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Reasoning about actions and state changes by injecting commonsense knowledge
Tandon, N.; Mishra, B. D.; Grus, J.; Yih, W.-t.; Bosselut, A.; and Clark, P. 2018 · 2018
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Commonsense knowledge in machine intelligence
Tandon, N.; Varde, A. S.; and de Melo, G. 2018 · 2018
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Dunn, M.; Sagun, L.; Higgins, M.; Guney, V. U.; Cirik, V.; and Cho, K. 2017 · 2017
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A formal theory of commonsense psychology: How people think people think
Gordon, A. S.; and Hobbs, J. R. 2017 · 2017
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Joshi, M.; Choi, E.; Weld, D. S.; and Zettlemoyer, L. 2017 · 2017
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Building machines that learn and think like people
Lake, B. M.; Ullman, T. D.; Tenenbaum, J. B.; and Gershman, S. J. 2017 · 2017
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Distilling the outcomes of personal experiences: A propensity-scored analysis of social media
Olteanu, A.; Varol, O.; and Kiciman, E. 2017 · 2017
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A data-driven text mining and semantic network analysis for design information retrieval
Shi, F.; Chen, L.; Han, J.; and Childs, P. 2017 · 2017
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Webchild 2.0: Fine-grained commonsense knowledge distillation
Tandon, N.; De Melo, G.; and Weikum, G. 2017 · 2017
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A simple method for commonsense reasoning
Trinh, T. H.; and Le, Q. V. 2018 · 2018
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COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
Bosselut, A.; Rashkin, H.; Sap, M.; Malaviya, C.; Celikyilmaz, A.; and Choi, Y. 2019 · 2019
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Scoring candidates using structural information in semi-structured documents for question answering systems
Fan, J. J.; and Ferrucci, D. A. 2019 · 2019
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Improving the robustness of question answering systems to question paraphrasing
Gan, W. C.; and Ng, H. T. 2019 · 2019
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Answer interaction in non-factoid question answering systems
Qu, C.; Yang, L.; Croft, W. B.; Scholer, F.; and Zhang, Y. 2019 · 2019
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Social IQA: Commonsense Reasoning about Social Interactions
Sap, M.; Rashkin, H.; Chen, D.; Le Bras, R.; and Choi, Y. 2019c · 2019
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K-BERT: Enabling Language Representation with Knowledge Graph
Liu, W.; Zhou, P.; Zhao, Z.; Wang, Z.; Ju, Q.; Deng, H.; and Wang, P. 2020 · 2020
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Commonsense Reasoning for Natural Language Processing
Sap, M.; Shwartz, V.; Bosselut, A.; Choi, Y.; and Roth, D. 2020 · 2020
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ConceptNet in Context
Speer, Robyn. 2020 · 2020
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IQA: Interactive query construction in semantic question answering systems
Zafar, H.; Dubey, M.; Lehmann, J.; and Demidova, E. 2020 · 2020
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