A starting point.
Direct Preference Optimization derives a preference-learning objective that avoids training a separate reward model in the studied setup.
What to keep in mind
Read the original paper for the experimental setting, baselines, and limitations; a result in one setting is not a guarantee of performance elsewhere.
This work is included in a researcher’s reading path. A detailed editorial explanation is still being prepared. The complete manuscript is available in Full paper.
Source: Direct Preference Optimization: Your Language Model is Secretly a Reward Model. The original manuscript contains the methods, experiments, figures, and references. An arXiv posting date may follow an earlier conference publication. Read the linked record for version history.