--- title: "Who cites Key-Point-Driven Data Synthesis — 41 citing papers" description: "41 papers of the Elamur Research library cite «Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning», found in…" canonical: "https://research.elamur.ai/free/en/papers/huang-2024-key-point-driven-data-synthesis/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/huang-2024-key-point-driven-data-synthesis/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Key-Point-Driven Data Synthesis with its…](https://md.research.elamur.ai/free/en/papers/huang-2024-key-point-driven-data-synthesis/) / cited by # Who cites «Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning» 41 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 «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/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 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. **[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* 4. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas arXiv:2406.20094**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/) 5. [**DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving arXiv:2407.13690**Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-dart-math-difficulty-aware-rejection/) 6. [**Rho-1: Not All Tokens Are What You Need arXiv:2404.07965**Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-rho-1-all-tokens-need/) 7. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/) 8. **[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* 9. **[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* 10. [**AI-Assisted Generation of Difficult Math Questions arXiv:2407.21009**Vedant Shah, Dingli Yu, Kaifeng Lyu, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shah-2024-ai-assisted-generation-difficult-math/) 11. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations* 12. [**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/) 13. **[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* 14. **[LogicPro: Improving Complex Logical Reasoning via Program-Guided Learning](https://md.research.elamur.ai/free/en/papers/jiang-2025-logicpro-improving-complex-logical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Jiang, Yuchen Yan, Yang Liu, et al.*2025 · 8 citations* 15. **[rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset](https://md.research.elamur.ai/free/en/papers/liu-2025-rstar-coder-scaling-competitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yifei Liu, Li Lyna Zhang, Yi Zhu, et al.*2025 · 8 citations* 16. **[A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianzhe Ma, Wenxuan Wang, Qin Jin*2026 · 1 citation* 17. **[FLAIR: Steering LLM Mathematical Problem Solving based on A Fuzzy-Logic-AssIsted Reasoner](https://md.research.elamur.ai/free/en/papers/wu-2026-flair-steering-llm-mathematical-problem/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wu, Hongru Sun, Wanqing Li, et al.*2026* 18. **[PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-personatrace-synthesizing-realistic-digital-footprints/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Minjia Wang, Yunfeng Wang, Xiao Ma, et al.*2026* 19. **[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* 20. **[Synthetic Data Generation for Training Diversified Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-synthetic-data-generation-training-diversified/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianhui Zhang, Bei Peng, Danushka Bollegala*2026* 21 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/huang-2024-key-point-driven-data-synthesis/) — Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning