Definition
What it means
RLHF typically gathers human preferences, learns a reward signal from them, and then optimizes a model to produce outputs that receive higher predicted reward.
Why it matters
Role in the system
It connects qualitative human judgment to an optimization process that can improve model behavior at scale.
Example
In practice
Reviewers compare assistant answers, and those rankings help train a reward model.