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Large language models (LLMs) have made significant progress in NLP.
Conceptnet—a practical commonsense reasoning tool-kit
Hugo Liu and Push Singh. 2004 · 2004
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Implicit and explicit knowledge about language
Nick C Ellis. 2008 · 2008
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The winograd schema challenge
Hector J Levesque, Ernest Davis, and Leora Morgenstern. 2012 · 2012
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Reporting bias and knowledge acquisition
Jonathan Gordon and Benjamin Van Durme. 2013 · 2013
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Establishing a human baseline for the winograd schema challenge
David Bender. 2015 · 2015
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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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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
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Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. 2018 · 2018
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Commonsense knowledge mining from pretrained models
Joe Davison, Joshua Feldman, and Alexander Rush. 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. 2019 · 2019
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CommonsenseQA: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2019 · 2019
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HellaSwag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 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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PIQA: reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan LeBras, Jianfeng Gao, and Yejin Choi. 2020 · 2020
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ProtoQA: A question answering dataset for prototypical common-sense reasoning
Michael Boratko, Xiang Li, Tim O’Gorman, Rajarshi Das, Dan Le, and Andrew McCallum. 2020 · 2020
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared 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 M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher 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 · 2020
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QASC: A dataset for question answering via sentence composition
Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, and Ashish Sabharwal. 2020 · 2020
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Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-Trained Language Models
Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, and Xiang Ren. 2020 · 2020
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Commonsense evidence generation and injection in reading comprehension
Ye Liu, Tao Yang, Zeyu You, Wei Fan, and Philip S. Yu. 2020 · 2020
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Do neural language models overcome reporting bias?
Vered Shwartz and Yejin Choi. 2020 · 2020
Cited alongside, same era.
Unsupervised commonsense question answering with self-talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2020
Cited alongside, same era.
Pre-training is (almost) all you need: An application to commonsense reasoning
Alexandre Tamborrino, Nicola Pellicanò, Baptiste Pannier, Pascal Voitot, and Louise Naudin. 2020 · 2020
Cited alongside, same era.
Connecting the dots: A knowledgeable path generator for commonsense question answering
Peifeng Wang, Nanyun Peng, Filip Ilievski, Pedro Szekely, and Xiang Ren. 2020 · 2020
Cited alongside, same era.
Evaluating commonsense in pre-trained language models
Xuhui Zhou, Yue Zhang, Leyang Cui, and Dandan Huang. 2020 · 2020
Cited alongside, same era.
Does pre-training induce systematic inference? how masked language models acquire commonsense knowledge
Ian Porada, Alessandro Sordoni, and Jackie Cheung. 2022 · 2022
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TSGP: Two-stage generative prompting for unsupervised commonsense question answering
Yueqing Sun, Yu Zhang, Le Qi, and Qi Shi. 2022 · 2022
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Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, et al. 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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Symbolic knowledge distillation: from general language models to commonsense models
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Explanations for CommonsenseQA: New Dataset and Models
Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, and Dinesh Garg. 2021 · 2021
Cited alongside, same era.
On commonsense cues in BERT for solving commonsense tasks
Leyang Cui, Sijie Cheng, Yu Wu, and Yue Zhang. 2021 · 2021
Cited alongside, same era.
“I’m not mad”: Commonsense implications of negation and contradiction
Liwei Jiang, Antoine Bosselut, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
Towards zero-shot commonsense reasoning with self-supervised refinement of language models
Tassilo Klein and Moin Nabi. 2021 · 2021
Cited alongside, same era.
Do language models learn commonsense knowledge?
Xiang Lorraine Li, Adhiguna Kuncoro, Cyprien de Masson d’Autume, Phil Blunsom, and Aida Nematzadeh. 2021 · 2021
Cited alongside, same era.
KG-BART: knowledge graph-augmented BART for generative commonsense reasoning
Ye Liu, Yao Wan, Lifang He, Hao Peng, and Philip S. Yu. 2021 · 2021
Cited alongside, same era.
Exploring strategies for generalizable commonsense reasoning with pre-trained models
Kaixin Ma, Filip Ilievski, Jonathan Francis, Satoru Ozaki, Eric Nyberg, and Alessandro Oltramari. 2021 · 2021
Cited alongside, same era.
Peter West, Chandra Bhagavatula, Jack Hessel, Jena Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, and Yejin Choi. 2022 · 2022
Later among the works it cites.
Alleviating the knowledge-language inconsistency: A study for deep commonsense knowledge
Yi Zhang, Lei Li, Yunfang Wu, Qi Su, and Xu Sun. 2022 · 2022
Later among the works it cites.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al. 2023 · 2023
Closest in time.
Language model behavior: A comprehensive survey
Tyler A Chang and Benjamin K Bergen. 2023 · 2023
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Qianglong Chen, Guohai Xu, Ming Yan, Ji Zhang, Fei Huang, Luo Si, and Yin Zhang. 2023 · 2023
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Anthony G Cohn and Jose Hernandez-Orallo. 2023 · 2023
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Free lunch for efficient textual commonsense integration in language models
Wanyun Cui and Xingran Chen. 2023 · 2023
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Benchmarks for automated commonsense reasoning: A survey
Ernest Davis. 2023 · 2023
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Buca: A binary classification approach to unsupervised commonsense question answering
Jie He, Víctor Gutiérrez-Basulto, Jeff Z Pan, et al. 2023 · 2023
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Commonsense knowledge transfer for pre-trained language models
Kazushi Kondo, Saku Sugawara, and Akiko Aizawa. 2023 · 2023
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A systematic study and comprehensive evaluation of chatgpt on benchmark datasets
Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, Md Amran Hossen Bhuiyan, Shafiq Joty, and Jimmy Xiangji Huang. 2023 · 2023
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Large language models are in-context semantic reasoners rather than symbolic reasoners
Xiaojuan Tang, Zilong Zheng, Jiaqi Li, Fanxu Meng, Song-Chun Zhu, Yitao Liang, and Muhan Zhang. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
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Large language models as commonsense knowledge for large-scale task planning
Zirui Zhao, Wee Sun Lee, and David Hsu. 2023 · 2023
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Commonsense knowledge transfer for pre-trained language models
Wangchunshu Zhou, Ronan Le Bras, and Yejin Choi. 2023 · 2023
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