DeepMind Researchers Introduce Reinforced Self-Training (ReST): A Simple algorithm for Aligning LLMs with Human Preferences Inspired by Growing Batch Reinforcement Learning (RL)

Large language models (LLMs) are outstanding at producing well-written content and resolving various linguistic problems. These models are trained using vast volumes of text and computation to increase the chance of the following token autoregressively. Former research, however, shows that creating text with high probability only sometimes corresponds well with human preferences on different tasks. […]

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