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We propose a general framework called Text Modular Networks(TMNs) for building interpretable systems that learn to solve complex tasks by decomposing them into simpler ones solvable by existing models.
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Learning a natural language interface with neural programmer
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Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth. 2018 · 2018
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Mapping to declarative knowledge for word problem solving
Subhro Roy and Dan Roth. 2018 · 2018
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The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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HotpotQA: A dataset for diverse, explainable multi-hop question answering
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