All terms

Reward Model

A separate model trained on human preference data, used to score how "good" a candidate AI response is during further training.

Once humans rank a set of model outputs, that ranking data trains a reward model - essentially an automated judge that can score millions of future outputs the way a human would have. The main model is then trained to maximize the reward model's score. This is the mechanism that turns a relatively small amount of human labeling into training signal at scale.

Example

After humans rank 10,000 pairs of responses, a reward model learns the pattern behind those rankings well enough to score a new, unseen response without a human present.

Common questions

No - as a contributor you produce the ranking/preference data; the lab's engineering team trains the reward model from it separately.

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