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Open book question answering is a subset of question answering tasks where the system aims to find answers in a given set of documents (open-book) and common knowledge about a topic.
The trec-8 question answering track report
Ellen M Voorhees et al · 1999
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The structure and performance of an open-domain question answering system
Dan Moldovan, Sanda Harabagiu, Marius Pasca, Rada Mihalcea, Roxana Girju, Richard Goodrum, and Vasile Rus · 2000
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An analysis of the askmsr question-answering system
Eric Brill, Susan Dumais, and Michele Banko · 2002
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Building watson: An overview of the deepqa project
David Ferrucci, Eric Brown, Jennifer Chu-Carroll, James Fan, David Gondek, Aditya A Kalyanpur, Adam Lally, J William Murdock, Eric Nyberg, John Prager, et al · 2010
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Summarization of yes/no questions using a feature function model
Jing He and Decheng Dai · 2011
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Mctest: A challenge dataset for the open-domain machine comprehension of text
Matthew Richardson, Christopher JC Burges, and Erin Renshaw · 2013
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Ask me anything: Dynamic memory networks for natural language processing
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, and Richard Socher · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi · 2016
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Dynamic memory networks for visual and textual question answering
Caiming Xiong, Stephen Merity, and Richard Socher · 2016
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer · 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
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Quac: Question answering in context
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, and Luke Zettlemoyer · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
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 · 2019
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Declarative question answering over knowledge bases containing natural language text with answer set programming
Arindam Mitra, Peter Clark, Oyvind Tafjord, and Chitta Baral · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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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 · 2019
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Coqa: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D Manning · 2019
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Looking beyond the surface: A challenge set for reading comprehension over multiple sentences
Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth · 2018
Cited alongside, same era.
Careful selection of knowledge to solve open book question answering
Pratyay Banerjee, Kuntal Kumar Pal, Arindam Mitra, and Chitta Baral · 2019
Cited alongside, same era.
Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al · 2019
Cited alongside, same era.
Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut · 2019
Cited alongside, same era.
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
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Quarel: A dataset and models for answering questions about qualitative relationships
Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, and Ashish Sabharwal · 2019
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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, et al · 2020
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Qa-gnn: Reasoning with language models and knowledge graphs for question answering
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, and Jure Leskovec · 2021
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