>Quite impressive results nevertheless!
How does it remain impressive? Is this just deference to the institutions of the authors? Or the general aura around AI/ML/DL?
A couple of years ago when FB trained some kind of architecture to compute derivatives by presenting it with problem,answer pairs I called it out as "just wrote memorization" and got promptly downvoted. Now here we have people using GPT3 (a network widely recognized to be just memorizing) for a similar task and people are still impressed? Like you said, their only insight was to augment the data and translate to a computable (parsable) form.
I'm guessing people don't understand what a papermill is, especially at these schools that have access to the gobs of compute that you need to make these projects go through. It's junk science - probably not reproducible, definitely not extensible, doesn't transfer out of the sample set - purely for the sake of incrementing publication count for all involved (cf. the number of authors on the paper). And before people label me a hater: I speak from experience as someone at one of these types of schools that has their name on several of the same sorts of "turn the crank" papers.