I think the point is more that in RL there's no ground truth to predict. So when training a model with RL the idea of "predicting" doesn't fit anymore. I'll make some edits I see that I wasn't very clear.
I feel like RLHF has a pretty obvious ground truth, human feedback is used as an (albeit noisy) signal of average human preferences. Same thing with RLVR and "solving the problem".
I feel like RLHF has a pretty obvious ground truth, human feedback is used as an (albeit noisy) signal of average human preferences. Same thing with RLVR and "solving the problem".