If a model can't inately reason over 5 steps in a simple task but produces a flawless 500 step proof you either have divine intervention or memorisation.
Also, AIMOv2 is doing stage 2 of their math challenge, they are now at "national olympics" level of difficulty. They have a new set of questions. Last year's winner (27/50 points) got 2/50 on the new set. In the first 3 weeks of the competition the top score is 10/50 on the new set, mostly with Qwen2.5-math. Given that this is a purposefully made new set of problems, and according to the organizers "made to be AI hard", I'd say the regurgitation stuff is getting pretty stale.
Also also, the fact that claude3.5 can start coding in an invented language w/ ~20-30k tokens of "documentation" about the invented language is also some kind of proof that the stochastic parrots are the dismissers in this case.
I'm not sure if it is feasible to provide all relevant sources to someone who doesn't follow a field. It is quite common knowledge that LLMs in their current form have no ability to recurse directly over a prompt, which inherently limits their reasoning ability.
I am not looking for all sources. And I do follow the field. I just don’t know the sources that would back the claim they are making. Nor do I understand why limits on recursion means there is no reasoning and only memorization.
The closest explanation to how chain of through works is suppressing the probability of a termination token.
People have found that even letting llms generate gibberish tokens produces better final outputs. Which isn't a surprise when you realise that the only way a llm can do computation is by outputting tokens.
Unless you are building one of the frontier models, I’m not sure that your experience gives you insight on those models. Perhaps it just creates needless assumptions.