Reinforcement Learning Fuels Advancements in Large Language Models
Reinforcement learning, fueled by a rapidly expanding open-source ecosystem with diverse libraries, is driving advancements in large language models, enabling optimization for properties like adoption, components like trainers and generators, and use cases like Reinforcement Learning from Human Feedback and multi-turn agentic RL.