#preference learning

Tagged preference learning · show all articles

A row of rater workstations in a bright annotation lab, the nearest screen showing one prompt above two candidate responses in side-by-side panes with neither of them chosen yet, an annotation guideline binder open on the desk and racks of training nodes standing behind

What RLHF Actually Optimises: Rated Agreeableness, and Where It Parts from Helpfulness

Reinforcement learning from human feedback does not install correctness. It fits a scalar model of what raters approved of and then pushes a policy up that surface — which is a different thing, in identifiable places.

By Brecht Corbeel · August 8, 2026 · 17 min read

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