Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation. (arXiv:2201.05088v1 [cs.CL])

Interpreting the predictions of existing Question Answering (QA) models is
critical to many real-world intelligent applications, such as QA systems for
healthcare, education, and finance. However, existing QA models lack
interpretability and provide no feedback or explanation for end-users to help
them understand why a specific prediction is the answer to a question.In this
research, we argue that the evidences of an answer is critical to enhancing the
interpretability of QA models. Unlike previous research that simply extracts
several sentence(s) …

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