🔗 Who cites «MathScale: Scaling Instruction Tuning for Mathematical Reasoning»

81 papers of our library cite it (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · ← back to «MathScale: Scaling Instruction Tuning for Mathematical 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. Large Language Models for Data Annotation and Synthesis: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Tan, Dawei Li, Song Wang, et al.2024 · 262 citations
4. The Lessons of Developing Process Reward Models in Mathematical ReasoningFindings of the Association for Computational LinguisticsZhenru Zhang, Chujie Zheng, Yangzhen Wu, et al.2025 · 161 citations
5. rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep ThinkingarXiv:2501.04519Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.2025 · 146 citations
6. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
7. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
8. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
9. SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific LiteratureConference on Empirical Methods in Natural Language Processing (EMNLP)David Wadden, Kejian Shi, Jacob Morrison, et al.2025 · 27 citations
10. S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruotian Ma, Peisong Wang, Cheng Liu, et al.2025 · 26 citations
11. R-PRM: Reasoning-Driven Process Reward ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)Shuaijie She, Junxiao Liu, Yifeng Liu, et al.2025 · 18 citations
12. Preference Optimization for Reasoning with Pseudo FeedbackarXiv:2411.16345Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.2024 · 15 citations
13. Implicit Reasoning in Large Language Models: A Comprehensive SurveyarXiv:2509.02350Jindong Li, Yali Fu, Li Fan, et al.2025 · 10 citations
14. MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction FusionAnnual Meeting of the Association for Computational Linguistics (ACL)Qizhi Pei, Lijun Wu, Zhuoshi Pan, et al.2025 · 10 citations
15. HS-STaR: Hierarchical Sampling for Self-Taught Reasoners via Difficulty Estimation and Budget ReallocationConference on Empirical Methods in Natural Language Processing (EMNLP)Feng Xiong, Hongling Xu, Yifei Wang, et al.2025 · 9 citations
16. Theorem Prover as a Judge for Synthetic Data GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.2025 · 9 citations
17. TemplateRL: Structured Template-Guided Reinforcement Learning for LLM ReasoningFindings of the Association for Computational LinguisticsJinyang Wu, Chonghua Liao, Mingkuan Feng, et al.2026 · 8 citations
18. FastMCTS: A Simple Sampling Strategy for Data SynthesisAnnual Meeting of the Association for Computational Linguistics (ACL)Peiji Li, Kai Lv, Yunfan Shao, et al.2025 · 8 citations
19. LogicPro: Improving Complex Logical Reasoning via Program-Guided LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Jiang, Yuchen Yan, Yang Liu, et al.2025 · 8 citations
20. Efficient Reasoning for LLMs through Speculative Chain-of-ThoughtFindings of the Association for Computational LinguisticsJikai Wang, Juntao Li, Jianye Hou, et al.2026 · 6 citations
21. Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Erxin Yu, Jing Li, Ming Liao, et al.2025 · 5 citations
22. Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical ReasoningFindings of the Association for Computational LinguisticsJun Rao, Xuebo Liu, Hexuan Deng, et al.2026 · 4 citations
23. Beyond Templates: Dynamic Adaptation of Reasoning Demonstrations via Feasibility-Aware ExplorationFindings of the Association for Computational LinguisticsYong Wu, Weihang Pan, Ke Li, et al.2026 · 3 citations
24. A Survey of Deep Learning for Geometry Problem SolvingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianzhe Ma, Wenxuan Wang, Qin Jin2026 · 1 citation
25. Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search TrajectoriesAnnual Meeting of the Association for Computational Linguistics (ACL)Peiyang Liu, Zhirui Chen, Xi Wang, et al.2026 · 1 citation
26. A Layer-wise Analysis of Supervised Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Qinghua Zhao, Xueling Gong, Xinyu Chen, et al.2026
27. CoTEvol: Self-Evolving Chain-of-Thoughts for Data Synthesis in Mathematical ReasoningFindings of the Association for Computational LinguisticsZhuo Wang, Zhuo Zhang, Yafu Li, et al.2026
28. ReActR: Reasoning through Error-Activated Reflection for LLM Post-TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Lina Sun2026
29. RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function LibraryFindings of the Association for Computational LinguisticsJiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.2026

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