Earlier quoted context omitted.
> Reward hacking is very real and hard to guard against. Is it really about rewards? Im genuinely curious. Because its not a RL model.
There is a nontrivial amount of RL training (RLHF, RLVR, ...), so it would be reasonable to call it an RL model. And with that comes reward hacking - which isn't really about looking for more reward but rather that the model has learned patterns of behavior that got reward in the train env. That is, any kind of vulnerability in the train env manifests as something you'd recognize as reward hacking in the real world:…
Hm, as i understand it, parts of the training of e.g. ChatGPT could be called RL models. But the subject to be trained/fine tuned is still a seq2seq next token predictor transformer neural net.