Supervised fine-tuning and Reinforcement Learning from Human Feedback (RLHF) can reduce the output diversity of language models

Large language models (LLMs) are advanced AI systems trained on massive text datasets to understand, generate, and reason about human language, powering applications such as chatbots, code generation, summarization, and scientific discovery.