eward-modeling
ability across the iterations. While this is only a preliminary study, we believe this is an
exciting avenue of research because this means the model is better able to assign rewards
in future iterations for improving instruction following – a kind of virtuous circle. While
this improvement likely saturates in realistic scenarios, it still allows for the possibility of
continual improvement beyond the human preferences that are typically used to build reward
models and instruction following m