🔗 Who cites «The Art of Scaling Reinforcement Learning Compute for LLMs»

19 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · ← back to «The Art of Scaling Reinforcement Learning Compute for LLMs»

1. REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage NormalizationarXiv:2501.03262Jian Hu, Jason Klein Liu, Haotian Xu, et al.2025 · 104 citations
2. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
3. KL for a KL: On-Policy Distillation with Control Variate BaselinearXiv:2605.07865Minjae Oh, Sangjun Song, Gyubin Choi, et al.2026 · 8 citations
4. The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Shu Zhou, Jinman Leng, Yufei Song, et al.2026

15 more papers of our library cite it; they have no page here yet.

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