You're right about the original GRPO proposal, but there are simplified variants that do just use best of K sampling.

GRPO (or GRPO like approaches) for diffusion/flow matching similarly can be likelihood free.

Without anchoring on the group average it's hardly Group-Relative and without likelihood there's no Policy; that doesn't leave much of the original GRPO unchanged...

Do you have a particular paper in mind that does likelihood-free best-of-K but just calls it GRPO?

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zimablue22 2 hours ago | parent [-]

Any of the Best of N papers that exploded in popularity after GRPO.

Likelihood is not fundamental to the spirit of GRPO, any exploratory mechanism would work.

That sequential LLMs have a step-wise probability is convenient but not critical to this approach (where rejection sampling is widely used in diffusion models).

	▲	kamranjon an hour ago \| parent [-]
		Do you have an example? Would love to read one.