Complex machine learning tasks such as question-answer and numerical reasoning will be easier to solve if they are decomposed into smaller functions that existing methods can solve. Based on this approach, a team of scientists from the Allen Institute for AI developed a general framework called the Text Modular Networks for interpretable systems. TNN, explained…

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