--- title: "Who cites NaturalReasoning: Reasoning in — 26 citing papers" description: "26 papers of the Elamur Research library cite «NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions», found in their…" canonical: "https://research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [NaturalReasoning: Reasoning in the Wild with 2.8M…](https://md.research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/) / cited by # Who cites «NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions» 26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions»](https://md.research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/) 1. **[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* 2. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/) 3. [**Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains arXiv:2507.17746**Anisha Gunjal, Anthony Wang, Elaine Lau, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/gunjal-2025-rubrics-rewards-reinforcement-learning-verifiable/) 4. **[WebThinker: Empowering Large Reasoning Models with Deep Research Capability](https://md.research.elamur.ai/free/en/papers/li-2025-webthinker-empowering-large-reasoning-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.*2025 · 72 citations* 5. [**Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models arXiv:2502.17387**Alon Albalak, Duy Phung, Nathan Lile, et al.*2025 · 43 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2025-big-math-large-scale-high/) 6. [**A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility arXiv:2504.07086**Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/hochlehnert-2025-sober-look-progress-language-model/) 7. **[Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization](https://md.research.elamur.ai/free/en/papers/zhang-2025-right-question-already-half-answer/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Qingyang Zhang, Haitao Wu, Changqing Zhang, et al.*2025 · 31 citations* 8. **[Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://md.research.elamur.ai/free/en/papers/akter-2026-nemotron-crossthink-scaling-self-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.*2026 · 9 citations* 9. **[NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2025-nover-incentive-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Liu, Siya Qi, Xinyu Wang, et al.*2025 · 7 citations* 10. [**Training AI Co-Scientists Using Rubric Rewards arXiv:2512.23707**Shashwat Goel, Rishi Hazra, Dulhan Jayalath, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/goel-2025-training-ai-co-scientists/) 11. **[MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2026-maestro-meta-learning-adaptive-estimation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Zhao, Hepeng Wang, Xiao Ding, et al.*2026 · 1 citation* 12. **[Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse Domains](https://md.research.elamur.ai/free/en/papers/su-2026-crossing-reward-bridge-expanding-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Su, Dian Yu, Linfeng Song, et al.*2026* 13. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026* 13 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yuan-2025-naturalreasoning-reasoning-wild-2-8m/) — NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions