Direct Preference Optimization (DPO)

A simplified alternative to RLHF for aligning language models with human preferences. DPO eliminates the need for training a separate reward model by directly optimizing the language model using preference pairs. DPO is computationally cheaper and more stable than RLHF while achieving comparable alignment results.