--- title: "Who cites MathPile: A Billion-Token-Scale — 46 citing papers" description: "46 papers of the Elamur Research library cite «MathPile: A Billion-Token-Scale Pretraining Corpus for Math», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [MathPile: A Billion-Token-Scale Pretraining…](https://md.research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/) / cited by # Who cites «MathPile: A Billion-Token-Scale Pretraining Corpus for Math» 46 papers of our library cite it (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · [← back to «MathPile: A Billion-Token-Scale Pretraining Corpus for Math»](https://md.research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/) 1. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,115 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/) 2. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct arXiv:2308.09583**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 372 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/) 3. [**LIMO: Less is More for Reasoning arXiv:2502.03387**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 209 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/) 4. **[MAmmoTH2: Scaling Instructions from the Web](https://md.research.elamur.ai/free/en/papers/yue-2024-mammoth2-scaling-instructions-web/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiang Yue, Tuney Zheng, Ge Zhang, et al.*2024 · 96 citations* 5. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/) 6. [**DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning arXiv:2504.11456**Zhiwei He, Tian Liang, Jiahao Xu, et al.*2025 · 78 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-deepmath-103k-large-scale-challenging/) 7. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/) 8. [**Learning From Mistakes Makes LLM Better Reasoner arXiv:2310.20689**Shengnan An, Zexiong Ma, Zeqi Lin, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-learning-mistakes-makes-llm-better/) 9. [**A Survey on Deep Learning for Theorem Proving arXiv:2404.09939**Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-survey-deep-learning-theorem-proving/) 10. **[Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/huang-2024-key-point-driven-data-synthesis/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yiming Huang, Xiao Liu, Yeyun Gong, et al.*2024 · 45 citations* 11. **[AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling](https://md.research.elamur.ai/free/en/papers/liu-2025-acemath-advancing-frontier-math-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Liu, Yang Chen, Mohammad Shoeybi, et al.*2025 · 37 citations* 12. **[JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models](https://md.research.elamur.ai/free/en/papers/zhou-2024-jiuzhang3-0-efficiently-improving-mathematical/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kun Zhou, Beichen Zhang, Jiapeng Wang, et al.*2024 · 29 citations* 13. **[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* 14. [**Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning arXiv:2407.00782**Zimu Lu, Aojun Zhou, Ke Wang, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-step-controlled-dpo-leveraging-stepwise/) 15. [**MegaMath: Pushing the Limits of Open Math Corpora arXiv:2504.02807**Fan Zhou, Zengzhi Wang, Nikhil Ranjan, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-megamath-pushing-limits-open-math/) 16. [**MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code arXiv:2410.08196**Zimu Lu, Aojun Zhou, Ke Wang, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-mathcoder2-better-math-reasoning-continued/) 17. **[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* 18. **[StepHint: Multi-level Stepwise Hints Enhance Reinforcement Learning to Reason](https://md.research.elamur.ai/free/en/papers/zhang-2026-stephint-multi-level-stepwise-hints/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaiyi Zhang, Ang Lv, Jinpeng Li, et al.*2026 · 13 citations* 19. [**MIND: Math Informed syNthetic Dialogues for Pretraining LLMs arXiv:2410.12881**Syeda Nahida Akter, Shrimai Prabhumoye, John Kamalu, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/akter-2024-mind-math-informed-synthetic-dialogues/) 20. [**Unearthing Large Scale Domain-Specific Knowledge from Public Corpora arXiv:2401.14624**Zhaoye Fei, Yunfan Shao, Linyang Li, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/fei-2024-unearthing-large-scale-domain-specific/) 21. [**From Blind Solvers to Logical Thinkers: Benchmarking LLMs' Logical Integrity on Faulty Mathematical Problems arXiv:2410.18921**A M Muntasir Rahman, Junyi Ye, Wei Yao, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/rahman-2024-blind-solvers-logical-thinkers-benchmarking/) 22. **[SciPedia: Unlocking the Value of Scientific Data for Pre-training](https://md.research.elamur.ai/free/en/papers/qin-2026-scipedia-unlocking-value-scientific-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiwei Qin, Zhen Huang, Tiantian Mi, et al.*2026* 24 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2023-mathpile-billion-token-scale-pretraining/) — MathPile: A Billion-Token-Scale Pretraining Corpus for Math