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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»

  1. Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-ImprovementarXiv:2409.12122An Yang, Beichen Zhang, Binyuan Hui, et al.2024 · 417 citations
  2. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  3. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  4. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.2024 · 90 citations
  5. OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction DataarXiv:2410.01560Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.2024 · 85 citations
  6. Common 7B Language Models Already Possess Strong Math CapabilitiesarXiv:2403.04706Chen Li, Weiqi Wang, Jingcheng Hu, et al.2024 · 79 citations
  7. We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?arXiv:2407.01284Runqi Qiao, Qiuna Tan, Guanting Dong, et al.2024 · 65 citations
  8. Learning From Mistakes Makes LLM Better ReasonerarXiv:2310.20689Shengnan An, Zexiong Ma, Zeqi Lin, et al.2023 · 64 citations
  9. A Survey on Large Language Models for Mathematical ReasoningACM Computing SurveysPeng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.2025 · 26 citations

17 more papers of our library cite it; they have no page here yet.

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