Read before Generate! Faithful Long Form Question Answering with Machine Reading

Understand

Long-form question answering (LFQA) aims to generate a paragraph-length answer for a given question.

• While current work on LFQA using large pre-trained model for generation are effective at producing fluent and somewhat relevant content, one primary challenge lies in how to generate a faithful answer that has less hallucinated content.
• We propose a new end-to-end framework that jointly models answer generation and machine reading.
• The key idea is to augment the generation model with fine-grained, answer-related salient information which can be viewed as an emphasis on faithful facts.