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AI & Machine Learning · Advanced

Direct Preference Optimization (DPO)

A preference-tuning method that optimizes a model directly on preferred vs. rejected responses without a separate reward model.

Definition

DPO reformulates RLHF as a classification-style loss on preference pairs, making alignment simpler, cheaper and more stable than PPO-based RLHF.

Exam tip

DPO needs preference pairs but no reward model and no RL loop.

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