ExtraPhrase: Efficient Data Augmentation for Abstractive Summarization. (arXiv:2201.05313v1 [cs.CL])

Neural models trained with large amount of parallel data have achieved
impressive performance in abstractive summarization tasks. However, large-scale
parallel corpora are expensive and challenging to construct. In this work, we
introduce a low-cost and effective strategy, ExtraPhrase, to augment training
data for abstractive summarization tasks. ExtraPhrase constructs pseudo
training data in two steps: extractive summarization and paraphrasing. We
extract major parts of an input text in the extractive summarization step, and
obtain its diverse expressions with the paraphrasing step. …

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