Part 5: Preference Alignment with DPO (Direct Preference Optimization)
← Previous Chapter: Part 4: Knowledge Distillation | Series Hub | Next Chapter: Part 6: Enterprise vLLM Deployment → Answer-first: DPO aligns model outputs directly on paired preference datasets (Chosen vs Rejected) using a closed-form loss function, completely bypassing the instability and memory overhead of training a separate PPO reward model.