--- title: "Who cites Mutual Reasoning Makes Smaller — 71 citing papers" description: "71 papers of the Elamur Research library cite «Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers», found in their…" canonical: "https://research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Mutual Reasoning Makes Smaller LLMs Stronger…](https://md.research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/) / cited by # Who cites «Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers» 71 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers»](https://md.research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/) 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. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking arXiv:2501.04519**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/) 3. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/) 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. **[RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2025-rare-retrieval-augmented-reasoning-enhancement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hieu Tran, Zonghai Yao, Zhichao Yang, et al.*2025 · 20 citations* 6. **[Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-search-refine-during-think-facilitating/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yaorui Shi, Sihang Li, Chang Wu, et al.*2025 · 18 citations* 7. **[Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/yu-2025-back-attention-understanding-enhancing-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zeping Yu, Yonatan Belinkov, Sophia Ananiadou*2025 · 16 citations* 8. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations* 9. **[Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2025-marco-o1-v2-widening/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huifeng Yin, Yu Zhao, Minghao Wu, et al.*2025 · 8 citations* 10. **[DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree Traversal](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-dars-dynamic-action-re-sampling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, et al.*2025 · 4 citations* 11. **[Multi-LLM Collaborative Search for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/yang-2026-multi-llm-collaborative-search-complex/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sen Yang, Yafu Li, Wai Lam, et al.*2026 · 3 citations* 12. **[Efficient Multi-Agent System Training with Data Influence-Oriented Tree Search](https://md.research.elamur.ai/free/en/papers/shi-2026-efficient-multi-agent-system-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wentao Shi, Zichun Yu, Fuli Feng, et al.*2026 · 2 citations* 13. **[Think in Sentences: Explicit Sentence Boundaries Enhance Language Model's Capabilities](https://md.research.elamur.ai/free/en/papers/liu-2026-think-sentences-explicit-sentence-boundaries/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhichen Liu, Yongyuan Li, Yang Xu*2026 · 1 citation* 14. **[Reasoning with Memory: Adaptive Information Management for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/man-2026-reasoning-memory-adaptive-information-management/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hieu Man, Ro-ee Tal, Abhishek Kumar, et al.*2026* 15. **[Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation](https://md.research.elamur.ai/free/en/papers/mule-2026-teaching-language-models-forecast-research/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Srujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan*2026* 56 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/) — Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers