A fixed benchmark is the weak link here, so the authors freeze each learned evaluator inside an epoch and only swap it at checkpoints after ground-truth anchor tests. The coding result is modest but concrete, 71.7 percent versus 69.9 percent held-out pass rate with fewer tokens, and the paper-review section is where the incentives get sharper because accepted AI-written samples are replayed as adversarial cases.