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Right. This seems to be the latest in the “throw random stuff at the wall and see what sticks” series of generative ai papers.

I don’t know if I’m too stupid to understand or if truly this is just “add random stuff to prompt” dressed up in flowery academic language.

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Not surprising - from what I can tell, machine learning has been going down this route for a decade.

Anything involving the higher level abstractions (tensor flow / keras /whatever) is full of handwavy stuff about this or that activation function / number of layers / model architecture working the best and doing a trial error with a different component in the above if it doesn't. Closer to kids playing with legos than statistics.

I’ve actually noticed this in other areas too. Tons of them just swap parts out of existing works, maybe add a novel idea or two, then boom new proposed technique new paper. I remember when I first noticed it after learning to parse the academic nomenclature for a particular subject I was into at the time (SLAM) and feeling ripped off, but hey if you catch up with a subject it’s a good reading shortcut and helps zoom in on new ideas.

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