 reward model that, rather than
being frozen, is continually updating during LLM alignment, in order to avoid this bottleneck.
The key to such an approach is to develop an agent that possesses all the abilities desired
during training, rather than separating them out into distinct models such as a reward
model and a language model. In the same way that pretraining and multitasking training of
instruction following tasks allow task transfer by training on many tasks at once [Collobert
and Weston, 2008, Radfo