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Question answering models can use rich knowledge sources -- up to one hundred retrieved passages and parametric knowledge in the large-scale language model (LM).
Language models are few-shot learners
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Seeing things from a different angle:discovering diverse perspectives about claims
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Knowing more about questions can help: Improving calibration in question answering
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Enabling language models to fill in the blanks
Chris Donahue, Mina Lee, and Percy Liang. 2020 · 2005
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Is retriever merely an approximator of reader?
Sohee Yang and Minjoon Seo. 2020 · 2010
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Distilling knowledge from reader to retriever for question answering
Gautier Izacard and Edouard Grave. 2020 · 2012
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XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin. 2016 · 2016
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"why should i trust you?": Explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016 · 2016
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Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2017
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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 · 2017
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Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2018 · 2018
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Universal dependency parsing from scratch
Peng Qi, Timothy Dozat, Yuhao Zhang, and Christopher D. Manning. 2018 · 2018
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ELI5: Long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 2019
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MRQA 2019 shared task: Evaluating generalization in reading comprehension
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, and Danqi Chen. 2019 · 2019
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Natural questions: A benchmark for question answering research
T. Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur P. Parikh, C. Alberti, D. Epstein, Illia Polosukhin, J. Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
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Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, A. H. Miller, P. Lewis, A. Bakhtin, Y. Wu, and S. Riedel. 2019 · 2019
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Beat the ai: Investigating adversarial human annotation for reading comprehension
Max Bartolo, A Roberts, Johannes Welbl, Sebastian Riedel, and Pontus Stenetorp. 2020 · 2020
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Automatic fact-guided sentence modification
Darsh J. Shah, Tal Schuster, and Regina Barzilay. 2020 · 2020
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Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave. 2021 · 2021
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Hurdles to progress in long-form question answering
Kalpesh Krishna, Aurko Roy, and Mohit Iyyer. 2021 · 2021
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Question and answer test-train overlap in open-domain question answering datasets
Patrick Lewis, Pontus Stenetorp, and Sebastian Riedel. 2021 · 2021
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Entity-based knowledge conflicts in question answering
Shayne Longpre, Kartik Kumar Perisetla, Anthony Chen, Nikhil Ramesh, Chris DuBois, and Sameer Singh. 2021 · 2021
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Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
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Selective question answering under domain shift
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Dense passage retrieval for open-domain question answering
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Ambigqa: Answering ambiguous open-domain questions
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End-to-end training of multi-document reader and retriever for open-domain question answering
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