flâneur

GRPO++: Tricks for Making RL Actually Work

cameronrwolfe.substack.com · 9,351 words · saved by 2 readers

How to go from the vanilla GRPO algorithm to functional RL training at scale...

(from [1, 3, 4]) Recent research on large language models (LLMs) has been heavily focused on reasoning and reinforcement learning (RL). At the center of this research lies Group Relative Policy Optimization (GRPO) [13], the RL optimizer used to train most open-source reasoning models. The popularity of GRPO is enhanced by its conceptual simplicity and practical efficiency. However, the simplicity of GRPO can be deceptive—the vanilla GRPO algorithm has subtle issues that can hinder the RL training process, especially at scale. Solving the shortcomings of GRPO has become a popular research…

saved by

related reading