An armchair effort to redefine the goalposts and judge NLP, but proof is in the pudding. For now, large language models are the best flavor. NLP models are already useful even in this early stage.
Given the authors credentials and publication history [1] it's a bit disingenuous to call this an 'armchair effort'.
[1] https://scholar.google.com/citations?user=i5sEc1YAAAAJ&hl=en...
EDIT:
Specifically, self-citation is the biggest issue, though often there are very good reasons to do it. For example, if you are working on a new area there might not be a lot of work other than yours. However, mindless self-citation grows the number of citation at O(N), as your n^th paper cites the (n - 1) papers before it. The total citation count grows by O(N^2)).