Starting with the title of the paper, the authors find that Reflective Prompt Evolution can outperform Reinforcement Learning!!
Using LLMs to write and refine prompts (for another LLM to complete a task) is outperforming (!!) highly targeted gradient descent updates using cutting-edge RL algorithms!
GEPA makes three key innovations on how exactly we use LLMs to propose prompts for LLMs -- (1) Pareto Optimal Candidate Selection, (2) Reflective Prompt Mutation, and (3) System-Aware Merging for optimizing Compound AI Systems.
The authors further present how GEPA can be used for training at test-time, one of the most exciting directions AI is evolving in!
Here is my review of the paper! I hope you find it useful!
https://www.youtube.com/watch?v=czy7hvXIImE