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From RL Papers to Framework Code: Inclusion and Review in Seven Open-Source Training Frameworks

Taiheng Pan · 2026 · arXiv

DOI: 10.48550/arXiv.2610.28027 · open-access PDF

Chinese

练习者通过培训框架使用语言模型的增强学习方法,因此一个框架包含的方法是对其用户进行一个配置更改。我们测量了这种情况的频率。我们通过他们的承诺历史追踪了7个RL后培训的开源框架,并将它们链接到2025年1月至2026年6月的6939份筛选的arXiv论文。在1598份建议通用RL培训方法的论文中,37份至少达到了一个框架。

Machine translation (Meta M2M100); the English original follows.

Abstract

Practitioners use reinforcement learning methods for language models through training frameworks, so a method that a framework includes is one configuration change away for its users. We measure how often this happens. We trace seven open-source frameworks for RL post-training through their commit histories and link them to 6,939 screened arXiv papers from January 2025 to June 2026. Of 1,598 papers that propose a general RL training method, 37 reached at least one framework. Across five quarterly cohorts of papers, the number included within 180 days stayed between 5 and 7 while the cohorts gr

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Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange