Reliability of automated retry validation in open-ended domains

Determine the reliability of automated retry validation used in the R^3L reflect-then-retry framework when applied to open-ended domains with subjective evaluation criteria (for example, creative writing), where verification of improved retries cannot rely on objective ground-truth signals.

Background

R^3L synthesizes improved trajectories via a reflect-then-retry mechanism and relies on automated validation to verify that a retried trajectory achieves a higher reward than the original attempt. This validation assumes access to objective signals (e.g., environment rewards or answer correctness) to confirm improvement.

The authors’ experiments focus on domains with verifiable ground truth, such as agentic environments and mathematical reasoning, where automated verification is straightforward. However, in open-ended tasks with subjective criteria, such as creative writing, there is no clear objective measure to validate whether a retry is genuinely better, making the reliability of automated validation uncertain.