--- title: "Who cites Learning Math Reasoning from — 37 citing papers" description: "37 papers of the Elamur Research library cite «Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions», found…" canonical: "https://research.elamur.ai/free/en/papers/ni-2022-learning-math-reasoning-self-sampled/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ni-2022-learning-math-reasoning-self-sampled/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Learning Math Reasoning from Self-Sampled Correct…](https://md.research.elamur.ai/free/en/papers/ni-2022-learning-math-reasoning-self-sampled/) / cited by # Who cites «Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions» 37 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions»](https://md.research.elamur.ai/free/en/papers/ni-2022-learning-math-reasoning-self-sampled/) 1. [**Scaling Relationship on Learning Mathematical Reasoning with Large Language Models arXiv:2308.01825**Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-scaling-relationship-learning-mathematical-reasoning/) 2. [**Generating Sequences by Learning to Self-Correct arXiv:2211.00053**Sean Welleck, Ximing Lu, Peter West, et al.*2022 · 172 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2022-generating-sequences-learning-self-correct/) 3. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models arXiv:2312.06585**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/) 4. [**LEVER: Learning to Verify Language-to-Code Generation with Execution arXiv:2302.08468**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/) 5. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/) 6. [**V-STaR: Training Verifiers for Self-Taught Reasoners arXiv:2402.06457**Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2024-v-star-training-verifiers-self/) 7. **[Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations](https://md.research.elamur.ai/free/en/papers/chen-2024-breaking-language-barriers-multilingual-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nuo Chen, Zinan Zheng, Ning Wu, et al.*2024 · 86 citations* 8. [**TinyGSM: achieving >80% on GSM8k with small language models arXiv:2312.09241**Bingbin Liu, Sebastien Bubeck, Ronen Eldan, et al.*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-tinygsm-achieving-80-gsm8k-small/) 9. **[MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-mugglemath-assessing-impact-query-response/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengpeng Li, Zheng Yuan, Hongyi Yuan, et al.*2024 · 43 citations* 10. **[Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision](https://md.research.elamur.ai/free/en/papers/wang-2024-multi-step-problem-solving-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Yunxuan Li, Yuexin Wu, et al.*2024 · 43 citations* 11. **[mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models](https://md.research.elamur.ai/free/en/papers/lai-2024-mcot-multilingual-instruction-tuning-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huiyuan Lai, Malvina Nissim*2024 · 34 citations* 12. [**NExT: Teaching Large Language Models to Reason about Code Execution arXiv:2404.14662**Ansong Ni, Miltiadis Allamanis, Arman Cohan, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/) 13. **[L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2024-l2ceval-evaluating-language-code-generation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.*2024 · 27 citations* 14. **[StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2024-steptool-enhancing-multi-step-tool/) [ACM International Conference on Information and Knowledge Management (CIKM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-information-and-knowledge-management-cikm/)**Yuanqing Yu, Zhefan Wang, Weizhi Ma, et al.*2024 · 20 citations* 15. **[STaR-SQL: Self-Taught Reasoner for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/he-2025-star-sql-self-taught-reasoner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingqian He, Yongliang Shen, Wenqi Zhang, et al.*2025 · 17 citations* 16. [**Can Large Reasoning Models Self-Train? arXiv:2505.21444**Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/shafayat-2025-large-reasoning-models-self-train/) 17. **[Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-interactive-evolution-neural-symbolic-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.*2025 · 15 citations* 18. **[To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization](https://md.research.elamur.ai/free/en/papers/wang-2025-code-or-not-code-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haozhe Wang, Long Li, Chao Qu, et al.*2025 · 9 citations* 19 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/ni-2022-learning-math-reasoning-self-sampled/) — Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions