31 citations · 119 across the 7 of their papers we have counts for
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cs.CL2020★ 30 cited
Abstractive Summarization with Combination of Pre-trained Sequence-to-Sequence and Saliency Models
Itsumi Saito, Kyosuke Nishida, Kosuke Nishida +1
Pre-trained sequence-to-sequence (seq-to-seq) models have significantly improved the accuracy of several language generation tasks, including abstractive summarization. Although th…
cs.CL2020★ 24 cited
Length-controllable Abstractive Summarization by Guiding with Summary Prototype
Itsumi Saito, Kyosuke Nishida, Kosuke Nishida +5
We propose a new length-controllable abstractive summarization model. Recent state-of-the-art abstractive summarization models based on encoder-decoder models generate only one sum…