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TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising
[article]
2020
arXiv
pre-print
Text summarization aims to extract essential information from a piece of text and transform the text into a concise version. Existing unsupervised abstractive summarization models leverage recurrent neural networks framework while the recently proposed transformer exhibits much more capability. Moreover, most of previous summarization models ignore abundant unlabeled corpora resources available for pretraining. In order to address these issues, we propose TED, a transformer-based unsupervised
arXiv:2001.00725v3
fatcat:n4penvk2dven3nzj3s4q4c67z4