--- title: "Who cites Satori: Reinforcement Learning — 13 citing papers" description: "13 papers of the Elamur Research library cite «Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via…" canonical: "https://research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Satori: Reinforcement Learning with…](https://md.research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/) / cited by # Who cites «Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search» 13 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search»](https://md.research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/) 1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations* 2. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling arXiv:2502.06703**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/) 3. **[A Survey on Large Language Models for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-survey-large-language-models-mathematical/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Peng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.*2025 · 26 citations* 4. **[S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ma-2025-s-2-r-teaching-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruotian Ma, Peisong Wang, Cheng Liu, et al.*2025 · 26 citations* 5. **[SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud Detection via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-safe-qaq-end-end-slow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peidong Wang, Zhiming Ma, Xin Dai, et al.*2026 · 3 citations* 6. **[AdapThink: Adaptive Thinking Preferences for Reasoning Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-adapthink-adaptive-thinking-preferences-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenyue Xu, Xu Wan, Wei Wang, et al.*2026* 7. **[Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains](https://md.research.elamur.ai/free/en/papers/yuan-2026-knowledge-verification-exploring-rlvr-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghang Yuan, Zhefan Wang, Fang Hu, et al.*2026* 8. **[MedKInstruct: A Multimodal Knowledge Graph Based Framework for Multi-Hop and Hard-Negative Instruction Data Synthesis in MedVQA](https://md.research.elamur.ai/free/en/papers/wu-2026-medkinstruct-multimodal-knowledge-graph-based/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yinan Wu, Jihang Jin, Xuhao Bao, et al.*2026* 9. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026* 4 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/) — Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search