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Collecting supporting evidence from large corpora of text (e.g., Wikipedia) is of great challenge for open-domain Question Answering (QA).
Nogueira, R.; and Cho, K. 2019 · 1901
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Hierarchical Graph Network for Multi-hop Question Answering
Fang, Y.; Sun, S.; Gan, Z.; Pillai, R.; Wang, S.; and Liu, J. 2019 · 1911
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Unsupervised question decomposition for question answering
Perez, E.; Lewis, P.; Yih, W.-t.; Cho, K.; and Kiela, D. 2020 · 2002
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Dense Passage Retrieval for Open-Domain Question Answering
Karpukhin, V.; Oguz, B.; Min, S.; Wu, L.; Edunov, S.; Chen, D.; and Yih, W. 2020 · 2004
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End-to-end memory networks
Sukhbaatar, S.; Weston, J.; Fergus, R.; et al. 2015 · 2015
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Reading Wikipedia to Answer Open-Domain Questions
Chen, D.; Fisch, A.; Weston, J.; and Bordes, A. 2017 · 2017
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Semi-supervised classification with graph convolutional networks
Kipf, T. N.; et al. 2017 · 2017
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BI-DIRECTIONAL ATTENTION FLOW FOR MACHINE COMPREHENSION
Seo, M.; Kembhavi, A.; Farhadi, A.; and Hajishirzi, H. 2017 · 2017
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Quary Expansion Using Local and Global Document Analysis
Xu, J.; and Croft, W. B. 2017 · 2017
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Relational inductive biases, deep learning, and graph networks
Battaglia, P. W.; Hamrick, J. B.; Bapst, V.; Sanchez-Gonzalez, A.; Zambaldi, V.; Malinowski, M.; Tacchetti, A.; Raposo, D.; Santoro, A.; Faulkner, R.; et al. 2018 · 2018
Cited alongside, same era.
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Yang, Z.; Qi, P.; Zhang, S.; Bengio, Y.; Cohen, W. W.; Salakhutdinov, R.; and Manning, C. D. 2018 · 2018
Cited alongside, same era.
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Clark, K.; Luong, M.-T.; Le, Q. V.; and Manning, C. D. 2019 · 2019
Cited alongside, same era.
Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Das, R.; Dhuliawala, S.; Zaheer, M.; and McCallum, A. 2019a · 2019
Cited alongside, same era.
Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering
Das, R.; Godbole, A.; Kavarthapu, D.; Gong, Z.; Singhal, A.; Yu, M.; Guo, X.; Gao, T.; Zamani, H.; Zaheer, M.; and McCallum, A. 2019b · 2019
Latent Retrieval for Weakly Supervised Open Domain Question Answering
Lee, K.; et al. 2019 · 2019
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Multi-hop Reading Comprehension through Question Decomposition and Rescoring
Min, S.; Zhong, V.; Zettlemoyer, L.; and Hajishirzi, H. 2019 · 2019
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Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
Nie, Y.; et al. 2019 · 2019
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Matching the Blanks: Distributional Similarity for Relation Learning
Soares, L. B.; FitzGerald, N.; Ling, J.; and Kwiatkowski, T. 2019 · 2019
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Transformer-XH: Multi-Evidence Reasoning with eXtra Hop Attention
Zhao, C.; Xiong, C.; Rosset, C.; Song, X.; Bennett, P.; and Tiwary, S. 2019 · 2019
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Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.; Lee, K.; and Toutanova, K. 2019 · 2019
Cited alongside, same era.
Cognitive Graph for Multi-Hop Reading Comprehension at Scale
Ding, M.; Zhou, C.; Chen, Q.; Yang, H.; and Tang, J. 2019 · 2019
Cited alongside, same era.
Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
Feldman, Y.; and El-Yaniv, R. 2019 · 2019
Cited alongside, same era.
Asai, A.; Hashimoto, K.; Hajishirzi, H.; Socher, R.; and Xiong, C. 2020 · 2020
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Differentiable Reasoning over a Virtual Knowledge Base
Dhingra, B.; Zaheer, M.; Balachandran, V.; Neubig, G.; Salakhutdinov, R.; and Cohen, W. W. 2020 · 2020
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Break it down: A question understanding benchmark
Wolfson, T.; Geva, M.; Gupta, A.; Gardner, M.; Goldberg, Y.; Deutch, D.; and Berant, J. 2020 · 2020
Closest in time.