rd et al., 2019, Ouyang et al., 2022], incorporating the reward
model into that same system allows task transfer between the reward modeling task and the
instruction following tasks.
We thus introduce Self-Rewarding Language Models, agents that both (i) act as instruction
following models generating responses for given prompts; and (ii) can generate and evaluate
new instruction following examples to add to their own training set. We train these models
using an Iterative DPO framework similar to that recentl