You might already know this, but a large part of test-time compute / 'overthinking' is just letting the model do more passes, and refine its activation residuals more.

For example, even if you make thinking tokens literally just '....' (absolutely meaningless; zero information), you still see significant performance improvements: https://arxiv.org/abs/2404.15758 and https://arxiv.org/abs/2607.22925 for some starters.

Treat thinking more like a "loading screen message" that's been RL'd to somewhat resemble its actual internal state; which happens in its activations, not tokens.

> For example, even if you make thinking tokens literally just

Generally speaking yes, but actually no (just randomness is suboptimal, adding steps just to add steps is suboptimal). There is a mechanism working there (in having a CoT) that is not quite clear.

The task is to optimize the efficiency of CoT. Understanding that it is not a plain "chain of thought" is the start of the problem, the solution is not there yet.

If we had the solution, there would exist no overthinking - CoT would be optimal (lean and essential plus best results).

Yeah I understand, it's my assumption that the actually/wait/but have a point. It doesn't reduce the fact that it increases the time for tasks substantially.