--- title: "Who cites Revisiting the Test-Time Scaling — 32 citing papers" description: "32 papers of the Elamur Research library cite «Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling…" canonical: "https://research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Revisiting the Test-Time Scaling of o1-like…](https://md.research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/) / cited by # Who cites «Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?» 32 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «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/) 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. [**ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning arXiv:2504.01296**Bairu Hou, Yang Zhang, Jiabao Ji, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-thinkprune-pruning-long-chain-thought/) 3. [**Efficient Reasoning Models: A Survey arXiv:2504.10903**Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-efficient-reasoning-models-survey/) 4. [**DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models arXiv:2505.13975**Yuxuan Jiang, Dawei Li, Francis Ferraro*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2025-drp-distilled-reasoning-pruning-skill/) 5. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations* 6. **[RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals](https://md.research.elamur.ai/free/en/papers/zhang-2025-rot-enhancing-table-reasoning-iterative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuanliang Zhang, Dingzirui Wang, Keyan Xu, et al.*2025 · 10 citations* 7. **[Language of Thought Shapes Output Diversity in Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-language-thought-shapes-output-diversity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoyang Xu, Wenxuan Zhang*2026 · 2 citations* 8. **[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* 9. **[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* 10. **[Format-Adapter: Improving Reasoning Capability of LLMs by Adapting Suitable Format](https://md.research.elamur.ai/free/en/papers/wang-2026-format-adapter-improving-reasoning-capability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dingzirui Wang, Xuanliang Zhang, Rongyu Cao, et al.*2026* 11. **[RFS-Guard: Detecting Reasoning Hallucinations via Cross-Phase Routing Focus in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-rfs-guard-detecting-reasoning-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihang Liu, Fang Zhouhua, Hui Liu, 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/zeng-2025-revisiting-test-time-scaling-o1/) — Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?