GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

GEPA is a SUPER exciting advancement for DSPy and a new generation of optimization algorithms re-imagined with LLMs!

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