Yes, the noising-denoising steps in this approach are summarizing-extending. The idea is that (unlike images) any piece of text lies somewhere on the length sca

Yes, the noising-denoising steps in this approach are summarizing-extending. The idea is that (unlike images) any piece of text lies somewhere on the length scale, like a fractal. You could take the whole text and treat it as a large scale object, or take shorter sentences and treat them on the short scale. What you are right in, is that you need a dataset of things being described twice. Like abstracts and papers, or messages and tldr's.