Direct Preference Optimization: Why You Can Align a Model Without a Reward Model
Reinforcement learning from human feedback, usually shortened to RLHF, made modern chat models usable. It also made them complicated. The standard pipeline trains a reward model on human preferences, then optimises a language model against that reward model with a reinforcement learning algorithm,…
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- 2026-10-28 08:14 · DEV Community — Machine Learning
Direct Preference Optimization: Why You Can Align a Model Without a Reward Model