--- title: "Who cites Recursive Introspection: Teaching — 56 citing papers" description: "56 papers of the Elamur Research library cite «Recursive Introspection: Teaching Language Model Agents How to Self-Improve», found in their…" canonical: "https://research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Recursive Introspection: Teaching Language Model…](https://md.research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/) / cited by # Who cites «Recursive Introspection: Teaching Language Model Agents How to Self-Improve» 56 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Recursive Introspection: Teaching Language Model Agents How to Self-Improve»](https://md.research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/) 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. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/) 3. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/) 4. [**O1 Replication Journey: A Strategic Progress Report — Part 1 arXiv:2410.18982**Yiwei Qin, Xuefeng Li, Haoyang Zou, et al.*2024 · 86 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-o1-replication-journey-strategic-progress/) 5. [**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/) 6. **[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* 7. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations* 8. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations* 9. [**ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning arXiv:2501.06590**Xiangru Tang, Tianyu Hu, Muyang Ye, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-chemagent-self-updating-library-large/) 10. **[MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/park-2025-maporl-multi-agent-post-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chanwoo Park, Seungju Han, Xingzhi Guo, et al.*2025 · 15 citations* 11. [**PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier arXiv:2506.10406**Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2025-pag-multi-turn-reinforced-llm/) 12. [**Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety**Qian Shen, Fanghua Cao, Min Yao, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shen-2026-children-s-english-reading-story/) 13. **[Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-examples-automated-thought-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinyang Wu, Mingkuan Feng, Shuai Zhang, et al.*2026* 43 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/) — Recursive Introspection: Teaching Language Model Agents How to Self-Improve