DPO (Direct Preference Optimization) and GRPO (Group Relative Policy Optimization) are both powerful LLM fine-tuning techniques that allow models to be tuned towards generating better responses. While GRPO is a Reinforcement Learning algorithm that requires much more setup, DPO is usually much easier to experiment with. So how feasible is it to build an RL-like training pipeline with just DPO?
