--- title: "Who cites DeepSeek-R1 Thoughtology: — 47 citing papers" description: "47 papers of the Elamur Research library cite «DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [DeepSeek-R1 Thoughtology: Let's think about LLM…](https://md.research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/) / cited by # Who cites «DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning» 47 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · [← back to «DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning»](https://md.research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/) 1. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/) 2. **[The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity](https://md.research.elamur.ai/free/en/papers/shojaee-2025-illusion-thinking-understanding-strengths-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.*2025 · 104 citations* 3. [**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/) 4. **[START: Self-taught Reasoner with Tools](https://md.research.elamur.ai/free/en/papers/li-2025-start-self-taught-reasoner-tools/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chengpeng Li, Mingfeng Xue, Zhenru Zhang, et al.*2025 · 21 citations* 5. **[REARANK: Reasoning Re-ranking Agent via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2025-rearank-reasoning-re-ranking-agent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Le Zhang, Bo Wang, Xipeng Qiu, et al.*2025 · 12 citations* 6. [**Guiding Reasoning in Small Language Models with LLM Assistance arXiv:2504.09923**Yujin Kim, Euiin Yi, Minu Kim, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-guiding-reasoning-small-language-models/) 7. **[Thinking Out Loud: Do Reasoning Models Know When They're Right?](https://md.research.elamur.ai/free/en/papers/zeng-2025-thinking-out-loud-do-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.*2025 · 9 citations* 8. **[Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode Theory](https://md.research.elamur.ai/free/en/papers/li-2025-understanding-thinking-process-reasoning-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ming Li, Nan Zhang, Chenrui Fan, et al.*2025 · 6 citations* 9. [**What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT arXiv:2509.19284**Yunzhen Feng, Julia Kempe, Cheng Zhang, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-characterizes-effective-reasoning-revisiting-length/) 10. **[Controllable LLM Reasoning via Sparse Autoencoder-Based Steering](https://md.research.elamur.ai/free/en/papers/fang-2026-controllable-llm-reasoning-sparse-autoencoder/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Fang, Wenjie Wang, Mingfeng Xue, et al.*2026 · 3 citations* 11. **[Coordinates from Context: Using LLMs to Ground Complex Location References](https://md.research.elamur.ai/free/en/papers/masis-2026-coordinates-context-llms-ground-complex/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tessa Masis, Brendan O'Connor*2026 · 1 citation* 12. **[Inferring Events from Time Series using Language Models](https://md.research.elamur.ai/free/en/papers/tan-2026-inferring-events-time-series-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingtian Tan, Mike A Merrill, Zachary Gottesman, et al.*2026 · 1 citation* 13. **[ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoningguard-safeguarding-large-reasoning-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuquan Wang, Mi Zhang, Yining Wang, et al.*2026 · 1 citation* 14. **[Thinking Long, but Short: Stable Sequential Test-Time Scaling for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/metel-2026-thinking-long-but-short-stable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michael R. Metel, Yufei Cui, Boxing Chen, et al.*2026 · 1 citation* 15. [**Language Specific Knowledge: Do Models Know Better in X than in English? arXiv:2505.14990**Ishika Agarwal, Nimet Beyza Bozdag, Dilek Hakkani-Tur*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-language-specific-knowledge-models-know/) 16. **[Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026* 17. **[RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-rit-rubrics-thinking-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Tian, Shuai Yuan, Muyun Ding, et al.*2026* 30 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/marjanovic-2025-deepseek-r1-thoughtology-let-s/) — DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning