--- title: "Who cites OlympicArena: Benchmarking — 47 citing papers" description: "47 papers of the Elamur Research library cite «OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI»…" canonical: "https://research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [OlympicArena: Benchmarking Multi-discipline…](https://md.research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/) / cited by # Who cites «OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI» 47 papers of our library cite it (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · [← back to «OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI»](https://md.research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/) 1. **[s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 608 citations* 2. **[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* 3. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/) 4. [**O1 Replication Journey: A Strategic Progress Report — Part 1 arXiv:2410.18982**Yiwei Qin, Xuefeng Li, Haoyang Zou, et al.*2024 · 86 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-o1-replication-journey-strategic-progress/) 5. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/) 6. [**DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning arXiv:2504.11456**Zhiwei He, Tian Liang, Jiahao Xu, et al.*2025 · 78 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-deepmath-103k-large-scale-challenging/) 7. **[RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement](https://md.research.elamur.ai/free/en/papers/jiang-2025-rag-star-enhancing-deliberative-reasoning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jinhao Jiang, Jiayi Chen, Junyi Li, et al.*2025 · 31 citations* 8. **[Unlocking Exploration in RLVR: Uncertainty-aware Advantage Shaping for Deeper Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2026-unlocking-exploration-rlvr-uncertainty-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Can Xie, Ruotong Pan, Xiangyu Wu, et al.*2026 · 15 citations* 9. **[Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks](https://md.research.elamur.ai/free/en/papers/li-2025-can-we-further-elicit-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingxuan Li, Weiwen Xu, Ruochen Zhao, et al.*2025 · 13 citations* 10. **[Towards Stable and Effective Reinforcement Learning for Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-effective-reinforcement-learning-mixture/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Di Zhang, Xun Wu, Shaohan Huang, et al.*2026 · 1 citation* 11. **[AAPO: Enhancing the Reasoning Capabilities of LLMs with Advantage Margin](https://md.research.elamur.ai/free/en/papers/xiong-2026-aapo-enhancing-reasoning-capabilities-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jian Xiong, Jingbo Zhou, Jingyong Ye, et al.*2026* 12. **[AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?](https://md.research.elamur.ai/free/en/papers/sun-2026-algbench-what-extent-do-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Henan Sun, Kaichi Yu, Yuyao Wang, et al.*2026* 13. **[Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-distributional-clarity-hidden-driver-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoning Sun, Mingzhu Cai, Huang He, et al.*2026* 14. **[Improved Policy Optimization for Mixture-of-Experts Models: Importance Sampling and Rewarding from an Expert-Centric Perspective](https://md.research.elamur.ai/free/en/papers/qian-2026-improved-policy-optimization-mixture-experts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yining Qian, Jinpeng Li, Fei Mi, et al.*2026* 15. **[RIFT: Repurposing Negative Samples via Reward-Informed Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-rift-repurposing-negative-samples-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zehua Liu, Shuqi Liu, Tao Zhong, et al.*2026* 16. **[SciPedia: Unlocking the Value of Scientific Data for Pre-training](https://md.research.elamur.ai/free/en/papers/qin-2026-scipedia-unlocking-value-scientific-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiwei Qin, Zhen Huang, Tiantian Mi, et al.*2026* 31 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-olympicarena-benchmarking-multi-discipline-cognitive/) — OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI