Valid Stopping in Adaptive Generator-Verifier Loops

We validate the approach in synthetic settings and on a protein-design benchmark. It comes from a paper posted to arXiv on 7 October 2026. Numerous agentic workflows are based on a generator-verifier loop: a generator proposes candidates, a cheap verifier scores them, and the workflow terminates when a proposal is verified as good enough. The verifier typically proxies a more costly ground-truth oracle, and as the generator searches adaptively against it, false acceptances may accumulate. Proposals can pass the proxy but fail under the costlier ground-truth check. We study when to stop these loops while controlling the false discovery rate of the accepted proposals. Our construction introduces tools of independent interest in distribution-free statistical testing and conformal risk control, including analysis of $e$-values constructed through index betting and a novel conformal risk control procedure for non-monotone losses.

Why it counts

We validate the approach in synthetic settings and on a protein-design benchmark.

Sources

Primary source: primary source

What is not known

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