---
title: "Who cites The Art of Scaling Reinforcement — 19 citing papers"
description: "19 papers of the Elamur Research library cite «The Art of Scaling Reinforcement Learning Compute for LLMs», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/khatri-2025-art-scaling-reinforcement-learning-compute/cited-by/"
---
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# 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»](https://md.research.elamur.ai/free/en/papers/khatri-2025-art-scaling-reinforcement-learning-compute/)

1. [**REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization arXiv:2501.03262**Jian Hu, Jason Klein Liu, Haotian Xu, et al.*2025 · 104 citations*](https://md.research.elamur.ai/free/en/papers/hu-2025-reinforce-stabilizing-critic-free-policy/)
2. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
3. [**KL for a KL: On-Policy Distillation with Control Variate Baseline arXiv:2605.07865**Minjae Oh, Sangjun Song, Gyubin Choi, et al.*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/oh-2026-kl-kl-policy-distillation-control/)
4. **[The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG](https://md.research.elamur.ai/free/en/papers/zhou-2026-retrieval-bottleneck-scaling-laws-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shu Zhou, Jinman Leng, Yufei Song, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/khatri-2025-art-scaling-reinforcement-learning-compute/) — The Art of Scaling Reinforcement Learning Compute for LLMs