Test-Time Self-Play：无需验证器的测试时扩展方法
Test-Time Self-Play: Scaling without a Verifier
做推理部署的可以看看：没有验证器也能做测试时扩展，在 LiveCodeBench 上无验证器时 mean@8 提升 35%，方法细节都在论文里。
arXiv 论文提出 Test-Time Self-Play（TTSP），一种不依赖验证器的测试时扩展方法，通过非对称自博弈改进大模型在难题上的表现。在 LiveCodeBench v6 的难度校准子集上，TTSP 在所有验证器强度下都是表现最好的方法，且验证器越弱与最强基线的差距越大。在完全没有验证器的条件下，TTSP 在 mean@8 上取得 35% 的绝对提升。唯一的例外是基础策略对正确答案的覆盖率接近零时收益消失。
Test-Time Self-Play: Scaling without a Verifier
Test-time scaling methods spend additional compute at deployment to improve a large language model's performance on a hard target problem. Most methods rely on a verifier that scores candidate solutions for correctness, using it to select among or refine the model's outputs. In many deployment regimes, however, a strong verifier on the target problem is unavailable. We introduce Test-Time Self-Play (TTSP), an approach to test-time scaling using asymmetric self-play without reliance on a verifier. On a difficulty-calibrated subset of LiveCodeBench v6, TTSP is the best-performing method at every verifier strength we evaluate, and the gap to the strongest baseline widens as the verifier weakens; in the no-verifier limit, TTSP yields a 35\% absolute improvement in mean@8. The gains hold across a range of verifier strengths, except when the base policy has near-zero coverage of the correct answer.