--- title: "Who cites MuggleMath: Assessing the — 37 citing papers" description: "37 papers of the Elamur Research library cite «MuggleMath: Assessing the Impact of Query and Response Augmentation on Math…" canonical: "https://research.elamur.ai/free/en/papers/li-2024-mugglemath-assessing-impact-query-response/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/li-2024-mugglemath-assessing-impact-query-response/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [MuggleMath: Assessing the Impact of Query and…](https://md.research.elamur.ai/free/en/papers/li-2024-mugglemath-assessing-impact-query-response/) / cited by # Who cites «MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning» 37 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← back to «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/) 1. [**Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement arXiv:2409.12122**An Yang, Beichen Zhang, Binyuan Hui, et al.*2024 · 417 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-qwen2-5-math-technical-report/) 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. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model arXiv:2502.02737**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 181 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/) 4. **[AlphaMath Almost Zero: Process Supervision without Process](https://md.research.elamur.ai/free/en/papers/chen-2024-alphamath-almost-zero-process-supervision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guoxin Chen, Minpeng Liao, Chengxi Li, et al.*2024 · 120 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. [**OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data arXiv:2410.01560**Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/toshniwal-2024-openmathinstruct-2-accelerating-ai-math/) 7. [**Common 7B Language Models Already Possess Strong Math Capabilities arXiv:2403.04706**Chen Li, Weiqi Wang, Jingcheng Hu, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-common-7b-language-models-already/) 8. **[OVM, Outcome-supervised Value Models for Planning in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2023-ovm-outcome-supervised-value-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fei Yu, Anningzhe Gao, Benyou Wang*2023 · 78 citations* 9. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/) 10. [**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/) 11. **[MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs](https://md.research.elamur.ai/free/en/papers/lu-2024-mathgenie-generating-synthetic-data-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zimu Lu, Aojun Zhou, Houxing Ren, et al.*2024 · 58 citations* 12. **[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* 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. **[SLAM: Towards Efficient Multilingual Reasoning via Selective Language Alignment](https://md.research.elamur.ai/free/en/papers/fan-2025-slam-efficient-multilingual-reasoning-selective/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuchun Fan, Yongyu Mu, YiLin Wang, et al.*2025 · 20 citations* 15. **[Neuro-Symbolic Data Generation for Math Reasoning](https://md.research.elamur.ai/free/en/papers/li-2024-neuro-symbolic-data-generation-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zenan Li, Zhi Zhou, Yuan Yao, et al.*2024 · 14 citations* 16. **[MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion](https://md.research.elamur.ai/free/en/papers/pei-2025-mathfusion-enhancing-mathematical-problem-solving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qizhi Pei, Lijun Wu, Zhuoshi Pan, et al.*2025 · 10 citations* 17. **[Long-Chain Reasoning Distillation via Adaptive Prefix Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-long-chain-reasoning-distillation-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenghao Liu, Zhuoyang Wu, Xinze Li, et al.*2026 · 3 citations* 18. **[Enhancing Long-Chain Reasoning Distillation through Error-Aware Self-Reflection](https://md.research.elamur.ai/free/en/papers/wu-2026-enhancing-long-chain-reasoning-distillation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyang Wu, Xinze Li, Zhenghao Liu, et al.*2026 · 1 citation* 19. **[ReActR: Reasoning through Error-Activated Reflection for LLM Post-Training](https://md.research.elamur.ai/free/en/papers/sun-2026-reactr-reasoning-through-error-activated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lina Sun*2026* 20. **[RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library](https://md.research.elamur.ai/free/en/papers/wang-2026-rv-syn-rational-verifiable-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.*2026* 17 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/li-2024-mugglemath-assessing-impact-query-response/) — MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning