🔗 Who cites «AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset»

49 papers of our library cite it (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · ← back to «AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset»

1. Kimi K2: Open Agentic IntelligencearXiv:2507.20534Kimi Team, Yifan Bai, Yiping Bao, et al.2025 · 347 citations
2. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
3. Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base ModelConference on Neural Information Processing Systems (NeurIPS)Jingcheng Hu, Yinmin Zhang, Qi Han, et al.2025 · 128 citations
4. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
5. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
6. DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing ReasoningarXiv:2504.11456Zhiwei He, Tian Liang, Jiahao Xu, et al.2025 · 78 citations
7. Llama-Nemotron: Efficient Reasoning ModelsarXiv:2505.00949Akhiad Bercovich, Itay Levy, Izik Golan, et al.2025 · 76 citations
8. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning ModelarXiv:2508.14444NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.2025 · 39 citations
9. AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yang Chen, Zhuolin Yang, Zihan Liu, et al.2025 · 30 citations
10. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
11. Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Sun, Yingqian Min, Zhipeng Chen, et al.2026 · 25 citations
12. AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL SynergyarXiv:2506.13284Zihan Liu, Zhuolin Yang, Yang Chen, et al.2025 · 21 citations
13. The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical ProofsarXiv:2506.21621Jasper Dekoninck, Ivo Petrov, Kristian Minchev, et al.2025 · 11 citations
14. Nemotron-Math: Efficient Long-Context Distillation of Mathematical Reasoning from Multi-Mode SupervisionarXiv:2512.15489Wei Du; Shubham Toshniwal; Branislav Kisacanin; Sadegh Mahdavi; Ivan Moshkov; George Armstrong; Stephen Ge; Edgar Minasyan; Feng Chen;, Igor Gitman2025 · 9 citations
15. Thinking Out Loud: Do Reasoning Models Know When They're Right?Conference on Empirical Methods in Natural Language Processing (EMNLP)Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.2025 · 9 citations
16. Front-Loading Reasoning: The Synergy between Pretraining and Post-Training DataarXiv:2510.03264Syeda Nahida Akter, Shrimai Prabhumoye, Eric Nyberg, et al.2025 · 6 citations
17. rStar2-Agent: Agentic Reasoning Technical ReportarXiv:2508.20722Ning Shang, Yifei Liu, Yi Zhu, et al.2025 · 6 citations
18. DeepPrune: Parallel Scaling without Inter-trace RedundancyFindings of the Association for Computational LinguisticsShangqing Tu, Yaxuan Li, Yushi Bai, et al.2026 · 3 citations
19. Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level TriggersFindings of the Association for Computational LinguisticsVan Yang, Shouren Wang, Debargha Ganguly, et al.2026 · 1 citation
20. AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African LanguagesAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Yu, Tianyi Xu, Michael A. Hedderich, et al.2026
21. Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain GeneralizationAnnual Meeting of the Association for Computational Linguistics (ACL)Tian Xueyun, MingHua Ma, Bingbing Xu, et al.2026
22. Learning to Refine: Self-Refinement of Parallel Reasoning in LLMsFindings of the Association for Computational LinguisticsQibin Wang, Pu Zhao, Shaohan Huang, et al.2026
23. On the Editability of Delta Parameters in Post-Trained ModelsFindings of the Association for Computational LinguisticsQiaoyu Tang, Le Yu, Bowen Yu, et al.2026
24. ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Peizhuo Lv, Ruihua Zhou, Yunpeng Li, et al.2026
25. Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Lechen Zhang, Yunxiang Zhang, Wei Hu, et al.2026
26. WildSci: Advancing Scientific Reasoning from In-the-Wild LiteratureFindings of the Association for Computational LinguisticsTengxiao Liu, Deepak Nathani, Zekun Li, et al.2026

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