Identifying the correct answer to a question often entails gathering large amounts of information and understanding complex ideas. In a recent study, a team of researchers at New York University (NYU) and Facebook AI Research (FAIR) investigated the possibility of automatically uncovering the underlying properties of problems such as question answering by examining how machine-learning models learn to solve related tasks.
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An approach to enhance question answering (QA) models
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