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We propose a system that finds the strongest supporting evidence for a given answer to a question, using passage-based question-answering (QA) as a testbed.
Evidence extraction for machine reading comprehension with deep probabilistic logic
Hai Wang, Dian Yu, Kai Sun, Jianshu Chen, Dong Yu, Dan Roth, and David McAllester. 2018a · 1902
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The importance of shape in early lexical learning
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Japanese and korean voice search
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Deep neural networks rival the representation of primate it cortex for core visual object recognition
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Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Eunsol Choi, Daniel Hewlett, Jakob Uszkoreit, Illia Polosukhin, Alexandre Lacoste, and Jonathan Berant. 2017 · 2017
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Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
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Attention is all you need
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What makes reading comprehension questions easier?
Saku Sugawara, Kentaro Inui, Satoshi Sekine, and Akiko Aizawa. 2018 · 2018
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FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
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Question answering as an automatic evaluation metric for news article summarization
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