What does Reinforcement Learning from Human Feedback (RLHF) mean? Definition | AI Understanding

Definition

A training method that uses human preference signals to shape model behavior.

Related terms

Reinforcement Learning

Training by reward signals where an agent learns actions that maximize long-term return.

A model that scores outputs based on preference signals, often used in RLHF pipelines.

DPO (Direct Preference Optimization)

A training method that fine-tunes models directly on preference pairs without needing a separate reward model.

Continual Learning

Training approaches that let a model keep learning from new data without forgetting prior knowledge.

Few-Shot Learning

Learning or adapting behavior from only a small number of examples.

Performance degradation over time as real-world conditions diverge from training assumptions.

Learn more in our free guides

Deep Learning Reinforcement Learning Machine Learning Basics Supervised Learning

See also

Retrieval Red Teaming Recommendation System Robustness Recall Safety Filter RAG (Retrieval-Augmented Generation)Scaling Law

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