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this seems really important:
it is totally plausible that a model could get IMO gold without *any* reinforcement learning, given a perfectly-crafted prompt
we just don't know, and lack tools to efficiently search through prompt space. glad to see at least someone is trying

29.7.2025
How does prompt optimization compare to RL algos like GRPO?
GRPO needs 1000s of rollouts, but humans can learn from a few trials—by reflecting on what worked & what didn't.
Meet GEPA: a reflective prompt optimizer that can outperform GRPO by up to 20% with 35x fewer rollouts!🧵

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