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Recently several datasets have been proposed to encourage research in Question Answering domains where commonsense knowledge is expected to play an important role.
Socialiqa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan LeBras, and Yejin Choi. 2019b · 1904
Earlier work this paper cites.
Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019a · 1907
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019b · 1907
Earlier work this paper cites.
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. 2019 · 1908
Earlier work this paper cites.
Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi. 2019 · 1911
Earlier work this paper cites.
Dbpedia: A nucleus for a web of open data
Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007 · 2007
Earlier work this paper cites.
Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Melissa Roemmele, Cosmin Adrian Bejan, and Andrew S Gordon. 2011 · 2011
Earlier work this paper cites.
Reporting bias and knowledge acquisition
Jonathan Gordon and Benjamin Van Durme. 2013 · 2013
Earlier work this paper cites.
MCTest: A challenge dataset for the open-domain machine comprehension of text
Matthew Richardson, Christopher J.C. Burges, and Erin Renshaw. 2013 · 2013
Earlier work this paper cites.
Elasticsearch: the definitive guide: a distributed real-time search and analytics engine
Clinton Gormley and Zachary Tong. 2015 · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Cited alongside, same era.
spacy 2: Natural language understanding with bloom embeddings, convolutional neural networks and incremental parsing
Matthew Honnibal and Ines Montani. 2017 · 2017
Cited alongside, same era.
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer. 2017 · 2017
Cited alongside, same era.
Race: Large-scale reading comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017
Cited alongside, same era.
Neural natural language inference models enhanced with external knowledge
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei. 2018 · 2018
Cited alongside, same era.
Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
Later among the works it cites.
Swag: A large-scale adversarial dataset for grounded commonsense inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz, and Yejin Choi. 2018 · 2018
Later among the works it cites.
Asu at textgraphs 2019 shared task: Explanation regeneration using language models and iterative re-ranking
Pratyay Banerjee. 2019 · 2019
Closest in time.
Careful selection of knowledge to solve open book question answering
Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra, and Chitta Baral. 2019 · 2019
Closest in time.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Closest in time.
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Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
Cited alongside, same era.
Wikihow: A large scale text summarization dataset
Mahnaz Koupaee and William Yang Wang. 2018 · 2018
Cited alongside, same era.
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
Cited alongside, same era.
Knowledgeable reader: Enhancing cloze-style reading comprehension with external commonsense knowledge
Todor Mihaylov and Anette Frank. 2018 · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Cited alongside, same era.
Wikiqa: A challenge dataset for open-domain question answering
Yi Yang, Wen-tau Yih, and Christopher Meek. 2015 · 2018
Cited alongside, same era.
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. 2019a
Cited in the paper.
What’s missing: A knowledge gap guided approach for multi-hop question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2019 · 2019
Closest in time.
Answering questions by learning to rank-learning to rank by answering questions
George Sebastian Pirtoaca, Traian Rebedea, and Stefan Ruseti. 2019 · 2019
Closest in time.
Coqa: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D Manning. 2019 · 2019
Closest in time.
Explicit utilization of general knowledge in machine reading comprehension
Chao Wang and Hui Jiang. 2019 · 2019
Closest in time.
Quick and (not so) dirty: Unsupervised selection of justification sentences for multi-hop question answering
Ved Prakash Yadav, Steven Bethard, and Mihai Surdeanu. 2019 · 2019
Closest in time.
Enhancing pre-trained language representations with rich knowledge for machine reading comprehension
An Yang, Quan Wang, Jing Liu, Kai Liu, Yajuan Lyu, Hua Wu, Qiaoqiao She, and Sujian Li. 2019 · 2019
Closest in time.