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Commonsense and background knowledge is required for a QA model to answer many nontrivial questions.
Multi-passage machine reading comprehension with cross-passage answer verification
Yizhong Wang, Kai Liu, Jing Liu, Wei He, Yajuan Lyu, Hua Wu, Sujian Li, and Haifeng Wang. 2018 · 1927
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Statistical theory of extreme values and some practical applications: a series of lectures
E.J. Gumbel. 1954 · 1954
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From freebase to wikidata: The great migration
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Robert Speer, Joshua Chin, and Catherine Havasi. 2016 · 2016
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Generating natural answers by incorporating copying and retrieving mechanisms in sequence-to-sequence learning
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World knowledge for reading comprehension: Rare entity prediction with hierarchical lstms using external descriptions
Bidirectional attention flow for machine comprehension
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Dynamic integration of background knowledge in neural NLU systems
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Leveraging knowledge bases in LSTMs for improving machine reading
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Commonsense for generative multi-hop question answering tasks
Lisa Bauer, Yicheng Wang, and Mohit Bansal. 2018 · 2018
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Natural answer generation with heterogeneous memory
Yao Fu and Yansong Feng. 2018 · 2018
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Knowledgeable reader: Enhancing cloze-style reading comprehension with external commonsense knowledge
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Product-aware answer generation in e-commerce question-answering
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