The data to be translated: DeepMind researchers have proposed the ReST algorithm, which aligns large language models with human preferences through incremental batch reinforcement learning. ReST filters samples generated by policies using a scoring function based on a reward model and optimizes the policy through an offline reinforcement learning objective within an inner loop. This algorithm aids in enhancing the performance and safety of language models across various tasks.