Paraphrase Generation as Unsupervised Machine Translation. (arXiv:2109.02950v2 [cs.CL] UPDATED)

In this paper, we propose a new paradigm for paraphrase generation by
treating the task as unsupervised machine translation (UMT) based on the
assumption that there must be pairs of sentences expressing the same meaning in
a large-scale unlabeled monolingual corpus. The proposed paradigm first splits
a large unlabeled corpus into multiple clusters, and trains multiple UMT models
using pairs of these clusters. Then based on the paraphrase pairs produced by
these UMT models, a unified surrogate model can be …

arxiv machine machine translation translation unsupervised