--- title: "Who cites Scaling of Search and Learning: A — 29 citing papers" description: "29 papers of the Elamur Research library cite «Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning…" canonical: "https://research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Scaling of Search and Learning: A Roadmap to…](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/) / cited by # Who cites «Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective» 29 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 «Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective»](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 2. **[Search-o1: Agentic Search-Enhanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/li-2025-search-o1-agentic-search-enhanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.*2025 · 211 citations* 3. **[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* 4. [**HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs arXiv:2412.18925**Junying Chen, Zhenyang Cai, Ke Ji, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-huatuogpt-o1-towards-medical-complex/) 5. [**DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Models arXiv:2503.04472**Yi Shen, Jian Zhang, Jieyun Huang, et al.*2025 · 57 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-dast-difficulty-adaptive-slow-thinking/) 6. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/) 7. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/) 8. **[Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?](https://md.research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2025 · 38 citations* 9. [**RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? arXiv:2501.11284**Haotian Xu, Xing Wu, Weinong Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-redstar-scaling-long-cot-data/) 10. [**InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models arXiv:2503.06692**Yuchen Yan, Yongliang Shen, Yang Liu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-inftythink-breaking-length-limits-long/) 11. [**Deconstructing Long Chain-of-Thought: A Structured Reasoning Optimization Framework for Long CoT Distillation arXiv:2503.16385**Yijia Luo, Yulin Song, Xingyao Zhang, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/luo-2025-deconstructing-long-chain-thought-structured/) 12. **[VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search](https://md.research.elamur.ai/free/en/papers/wang-2025-visuothink-empowering-lvlm-reasoning-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yikun Wang, Siyin Wang, Qinyuan Cheng, et al.*2025 · 13 citations* 13. [**Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RL arXiv:2505.17952**Che Liu, Haozhe Wang, Jiazhen Pan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-distillation-pushing-limits-medical-llm/) 14. [**A Survey on Feedback-based Multi-step Reasoning for Large Language Models on Mathematics arXiv:2502.14333**Ting-Ruen Wei, Haowei Liu, Xuyang Wu, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wei-2025-survey-feedback-based-multi-step/) 15. **[ARISE: An Adaptive Resolution-Aware Metric for Test-Time Scaling Evaluation in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2026-arise-adaptive-resolution-aware-metric/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyue Yin, Qiushi Sun, Zhiyuan Zeng, et al.*2026 · 1 citation* 16. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/) 13 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/) — Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective