Earlier quoted context omitted.
I assume they mean "Reinforcement Learning", and it's been a decade since I studied AI in university, but isn't it perfectly valid to just say "RL"? What kind of specificity are you looking for, whether they used Q-Learning or some other algorithm?
I wouldn’t phrase it as a matter of “validity”. I would phrase it as a question of transparency. Putting a model out in public without clearly explaining how it works doesn’t meet my bar for a proper scientific exchange of knowledge. Perhaps they are being intentionally vague for competitive reasons. RL is a generic term that can be mixed and matched with various other methods. In the context of LLMs, often some vari…
If you put it like that, I absolutely agree with you, except that I suppose I don't really consider this an exchange of knowledge but more like the release of an open-source project: the only thing they need to publish are instructions on how to use it. I don't think they’re really interested in anyone improving their model by themselves or reproducing the work. It would be amazing if they did, though!