{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Reinforcement Learning from Human Feedback — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"

AI Glossary — gaks.ai

Reinforcement Learning from Human Feedback (RLHF)

A training approach where a language model is fine-tuned using feedback from human raters who compare and rank model outputs. The human preferences are used to train a reward model, which then guides further training via reinforcement learning. RLHF has been central to making large language models more helpful, harmless, and honest.

Source: gaks.ai/glossary/reinforcement-learning-from-human-feedback →
"}