preference-learning

A deep dive into DPO (Rafailov et al. 2023) and its successors — how they reformulate RLHF as a classification problem, the math behind the implicit reward, and where each variant wins or loses against PPO-based pipelines.

Trace the full arc of Reinforcement Learning from Human Feedback — preference data, Bradley-Terry reward models, PPO with KL penalty, reward hacking, and why most labs have moved to offline alternatives like DPO and RAFT.