RLVR

“These reward models tend to have a lot of problems and you can over optimize them much more easily because the reward models will pick up on features that are maybe emojis or something like this that you don't actually care about where RLVR is much better matc…”

“It's similar to, you know, optimizers with Adam. So Adam is, I mean, right now there's Adam W. There was SGD and all the other RMS prop and how they were called. And they kind of all converge to Adam W by adding more and more tricks. And I think that's the sam…”

“The knowledge is already there in the pre-training, and this just unlocks it. It's just like a step that maybe shows the model how to use its own knowledge, basically.”

“I took the Quinn three model as part of my book, the reasoning from scratch book. And I trained it just for 50 steps with RLVR, and it goes from 15%, so one five percent accuracy on math 500 to 50% on math 500.”

“If you look, you know, if you fast forward a bit and you look at the, like the DeepSeq R-one paper where they effectively laid out, you know, what I think all the labs were doing at that time, or at least OpenAI was doing in terms of you know, RLVR reasoning f…”