[mdp2021]

I am not sure that fits the point, YGQ:

it seems to me the concept of «concept» in the paper is "the embedding vector we get in systems like SONAR (which we could use to generalize ordered sets of tokens into more complex ideas)". That's pretty specific, only marginally related to past handling as mentioned.

[YeGoblynQueenne]

That's only the representation of a concept. Different systems and different approaches will have different representations but that doesn't change the fact of what is being represented.

[mdp2021]

But if the issue is about "research in AI has had to deal with the concept of "concept" since the inception" (and of course it had to), the contribution in this paper is to try an operational implementation that could bear fruit and possibly fix architectural shortcomings of the mainstream effort.

(It is not separate from the context of LLMs.)

[YeGoblynQueenne]

Right, but there's been many operationalisations before. That's what's not new. Tome Mitchell's textbook has plenty of examples. Basically all of machine learning is about learning concepts- in practice as well as in theory. That's the whole point.