--- title: "Who cites Evolving Deeper LLM Thinking — 35 citing papers" description: "35 papers of the Elamur Research library cite «Evolving Deeper LLM Thinking», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/lee-2025-evolving-deeper-llm-thinking/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lee-2025-evolving-deeper-llm-thinking/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Evolving Deeper LLM Thinking](https://md.research.elamur.ai/free/en/papers/lee-2025-evolving-deeper-llm-thinking/) / cited by # Who cites «Evolving Deeper LLM Thinking» 35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «Evolving Deeper LLM Thinking»](https://md.research.elamur.ai/free/en/papers/lee-2025-evolving-deeper-llm-thinking/) 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. [**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. **[PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/parmar-2025-plangen-multi-agent-framework-generating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mihir Parmar, Xin Liu, Palash Goyal, et al.*2025 · 16 citations* 5. **[Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/sui-2026-meta-reasoner-dynamic-guidance-optimized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Sui, Yufei He, Tri Cao, et al.*2026 · 13 citations* 6. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/) 7. **[Language Modeling by Language Models](https://md.research.elamur.ai/free/en/papers/cheng-2025-language-modeling-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Junyan Cheng, Peter Clark, Kyle Richardson*2025 · 9 citations* 8. **[Problem Solving Through Human–AI Preference-based Cooperation](https://md.research.elamur.ai/free/en/papers/dutta-2025-problem-solving-through-human-ai/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, et al.*2025 · 9 citations* 9. **[AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment](https://md.research.elamur.ai/free/en/papers/wang-2026-alphacontext-evolutionary-tree-based-psychometric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Wang, Yue Huang, Hong Qian, et al.*2026* 10. **[CoTEvol: Self-Evolving Chain-of-Thoughts for Data Synthesis in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-cotevol-self-evolving-chain-thoughts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuo Wang, Zhuo Zhang, Yafu Li, et al.*2026* 11. **[Evolutionary Search for Automated Design of Uncertainty Quantification Methods](https://md.research.elamur.ai/free/en/papers/seleznyov-2026-evolutionary-search-automated-design-uncertainty/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.*2026* 12. **[Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality](https://md.research.elamur.ai/free/en/papers/zhang-2026-follow-path-reasoning-over-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhang, Johannes Bjerva, Russa Biswas*2026* 13. **[Parallel Test-Time Scaling for Latent Reasoning Models](https://md.research.elamur.ai/free/en/papers/you-2026-parallel-test-time-scaling-latent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runyang You, Yongqi Li, Meng Liu, et al.*2026* 14. **[Self-Consistency from Only Two Samples: CoT–PoT Ensembling for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/saparkhan-2026-self-consistency-only-two-samples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raman Saparkhan, Majd Hawasly, Md Rizwan Parvez, et al.*2026* 21 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/lee-2025-evolving-deeper-llm-thinking/) — Evolving Deeper LLM Thinking