Papers with unsupervised PEGASUS

1 papers
Unsupervised Summarization Re-ranking (2023.findings-acl)

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Challenge: Abstractive summarization models have been gaining popularity, but performance of unsupervised models still lags behind supervised models.
Approach: They propose to re-rank summary candidates in an unsupervised manner to close the performance gap between unsupervised and supervised models.
Outcome: The proposed model improves unsupervised models by up to 7.27% and ChatGPT by up 6.86% relative mean ROUGE across four widely-adopted summarization benchmarks.

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