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Integrating external knowledge into commonsense reasoning tasks has shown progress in resolving some, but not all, knowledge gaps in these tasks.
Roberta: A robustly optimized bert pretraining approach
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Zhi-Xiu Ye, Qian Chen, Wen Wang, and Zhen-Hua Ling. 2019 · 1908
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Dynamic knowledge graph construction for zero-shot commonsense question answering
Antoine Bosselut and Yejin Choi. 2019 · 1911
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Why do masked neural language models still need common sense knowledge?
Sunjae Kwon, Cheongwoong Kang, Jiyeon Han, and Jaesik Choi. 2019 · 1911
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Commongen: A constrained text generation challenge for generative commonsense reasoning
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What does my qa model know? devising controlled probes using expert knowledge
Kyle Richardson and Ashish Sabharwal. 2019 · 1912
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olmpics–on what language model pre-training captures
Alon Talmor, Yanai Elazar, Yoav Goldberg, and Jonathan Berant. 2019a · 1912
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Wordnet: a lexical database for english
George A Miller. 1995 · 1995
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A primer in bertology: What we know about how bert works
Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2020 · 2002
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Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, and Xiang Ren. 2020 · 2005
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Winowhy: A deep diagnosis of essential commonsense knowledge for answering winograd schema challenge
Hongming Zhang, Xinran Zhao, and Yangqiu Song. 2020 · 2005
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Pei Zhou, Rahul Khanna, Bill Yuchen Lin, Daniel Ho, Xiang Ren, and Jay Pujara. 2020a · 2005
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The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern. 2012 · 2012
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Neural natural language inference models enhanced with external knowledge
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei. 2017 · 2017
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
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Commonsense for generative multi-hop question answering tasks
Lisa Bauer, Yicheng Wang, and Mohit Bansal. 2018 · 2018
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Wikihow: A large scale text summarization dataset
Mahnaz Koupaee and William Yang Wang. 2018 · 2018
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Incorporating deep visual features into multiobjective based multi-view search results clustering
Sayantan Mitra, Mohammed Hasanuzzaman, Sriparna Saha, and Andy Way. 2018 · 2018
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Mcscript2. 0: A machine comprehension corpus focused on script events and participants
Simon Ostermann, Michael Roth, and Manfred Pinkal. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Explain yourself! leveraging language models for commonsense reasoning
Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Social iqa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan Le Bras, and Yejin Choi. 2019b · 2019
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Ernie: Enhanced representation through knowledge integration
Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, and Hua Wu. 2019 · 2019
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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
Cited alongside, same era.
Comet: Commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi. 2019 · 2019
Cited alongside, same era.
Understanding commonsense inference aptitude of deep contextual representations
Jeff Da and Jungo Kasai. 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
Cited alongside, same era.
Cosmos qa: Machine reading comprehension with contextual commonsense reasoning
Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2019 · 2019
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Kagnet: Knowledge-aware graph networks for commonsense reasoning
Bill Yuchen Lin, Xinyue Chen, Jamin Chen, and Xiang Ren. 2019a · 2019
Cited alongside, same era.
Towards generalizable neuro-symbolic systems for commonsense question answering
Kaixin Ma, Jonathan Francis, Quanyang Lu, Eric Nyberg, and Alessandro Oltramari. 2019 · 2019
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Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019b · 2019
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Improving question answering over incomplete kbs with knowledge-aware reader
Wenhan Xiong, Mo Yu, Shiyu Chang, Xiaoxiao Guo, and William Yang Wang. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V Le. 2019 · 2019
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From recognition to cognition: Visual commonsense reasoning
Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Ernie: Enhanced language representation with informative entities
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019 · 2019
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“Going on a vacation” takes longer than “Going for a walk”: A Study of Temporal Commonsense Understanding
Ben Zhou, Daniel Khashabi, Qiang Ning, and Dan Roth. 2019 · 2019
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Abductive commonsense reasoning
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, and Yejin Choi. 2020 · 2020
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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi. 2020 · 2020
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