Comment by garrinm

1 day ago

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".

  • To be more specific there’s no ground truth tokens to predict. There a verifiable answer in RLVR. But the tokens are explored. Not predicted as there’s no true token to predict.