--- title: "Mathematics & statistics — papers" description: "Mathematics & statistics: 161 papers of the Elamur Research library · page 1 of 7 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/mathematics/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/mathematics/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / Mathematics & statistics # ➗ Mathematics & statistics 161 papers · page 1 of 7 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Mathematics, proofs, computational mathematics, word problems and how machines learn to solve them, statistics. **1** [2](https://md.research.elamur.ai/free/en/shelves/mathematics/page/2/) … [7](https://md.research.elamur.ai/free/en/shelves/mathematics/page/7/) [next →](https://md.research.elamur.ai/free/en/shelves/mathematics/page/2/) - [DAPO: An Open-Source LLM Reinforcement Learning System at Scale](https://md.research.elamur.ai/free/en/papers/yu-2025-dapo-open-source-llm-reinforcement/) — Qiying Yu, Zheng Zhang, Ruofei Zhu, et al. · 2025 - [DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/) — Z. Z. Ren, Zhihong Shao, Junxiao Song, et al. · 2025 - [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deepseek-2025-ai-deepseek-r1-incentivizing-reasoning-capability/) — DeepSeek-AI, Daya Guo, Dejian Yang, et al. · 2025 - [Demystifying Long Chain-of-Thought Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/) — Edward Yeo, Yuxuan Tong, Morry Niu, et al. · 2025 - [Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/) — Yang Yue, Zhiqi Chen, Rui Lu, et al. · 2025 - [Group Sequence Policy Optimization](https://md.research.elamur.ai/free/en/papers/zheng-2025-group-sequence-policy-optimization/) — Chujie Zheng, Shixuan Liu, Mingze Li, et al. · 2025 - [Humanity's Last Exam](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/) — Long Phan, Alice Gatti, Ziwen Han, et al. · 2025 - [Kimi k1.5: Scaling Reinforcement Learning with LLMs](https://md.research.elamur.ai/free/en/papers/kimi-2025-team-kimi-k1-5-scaling-reinforcement/) — Kimi Team, Angang Du, Bofei Gao, et al. · 2025 - [LIMO: Less is More for Reasoning](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/) — Yixin Ye, Zhen Huang, Yang Xiao, et al. · 2025 - [Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model](https://md.research.elamur.ai/free/en/papers/hu-2025-open-reasoner-zero-open-source/) — Jingcheng Hu, Yinmin Zhang, Qi Han, et al. · 2025 - [OpenThoughts: Data Recipes for Reasoning Models](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/) — Etash Guha, Ryan Marten, Sedrick Keh, et al. · 2025 - [Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/) — Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al. · 2025 - [Process Reinforcement through Implicit Rewards](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/) — Ganqu Cui, Lifan Yuan, Zefan Wang, et al. · 2025 - [ProcessBench: Identifying Process Errors in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zheng-2025-processbench-identifying-process-errors-mathematical/) — Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al. · 2025 - [Qwen3 Technical Report](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen3-technical-report/) — An Yang, Anfeng Li, Baosong Yang, et al. · 2025 - [rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/) — Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al. · 2025 - [s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) — Niklas Muennighoff, Zitong Yang, Weijia Shi, et al. · 2025 - [SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild](https://md.research.elamur.ai/free/en/papers/zeng-2025-simplerl-zoo-investigating-taming-zero/) — Weihao Zeng, Yuzhen Huang, Qian Liu, et al. · 2025 - [SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/) — Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al. · 2025 - [The Lessons of Developing Process Reward Models in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-lessons-developing-process-reward-models/) — Zhenru Zhang, Chujie Zheng, Yangzhen Wu, et al. · 2025 - [Understanding R1-Zero-Like Training: A Critical Perspective](https://md.research.elamur.ai/free/en/papers/liu-2025-understanding-r1-zero-like-training/) — Zichen Liu, Changyu Chen, Wenjun Li, et al. · 2025 - [AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/) — Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al. · 2024 - [AlphaMath Almost Zero: Process Supervision without Process](https://md.research.elamur.ai/free/en/papers/chen-2024-alphamath-almost-zero-process-supervision/) — Guoxin Chen, Minpeng Liao, Chengxi Li, et al. · 2024 - [DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) — Jeffrey Li, Alex Fang, Georgios Smyrnis, et al. · 2024 - [DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-v1-5-harnessing/) — Huajian Xin, Z. Z. Ren, Junxiao Song, et al. · 2024 **1** [2](https://md.research.elamur.ai/free/en/shelves/mathematics/page/2/) … [7](https://md.research.elamur.ai/free/en/shelves/mathematics/page/7/) [next →](https://md.research.elamur.ai/free/en/shelves/mathematics/page/2/) - [← previous shelf Machine translation](https://md.research.elamur.ai/free/en/shelves/mtrans/) - [next shelf → Modern Hebrew](https://md.research.elamur.ai/free/en/shelves/he/) - [↑ back to shelves](https://md.research.elamur.ai/free/en/shelves/)