# Valid Stopping in Adaptive Generator-Verifier Loops

arXiv: https://arxiv.org/abs/2610.06432 · HTML: https://mlsanity.com/paper/2610.06432/

## Key facts

- No citing papers in the map yet (data through 7 Oct 2026).
- First posted on arXiv 5 Oct 2026.

## Placed in

- LLM agents and tool use

## Abstract (arXiv)

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