🔗 Who cites «Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning»

42 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 «Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning»

1. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
2. Stop Overthinking: A Survey on Efficient Reasoning for Large Language ModelsarXiv:2503.16419Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.2025 · 157 citations
3. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
4. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
5. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations
6. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
7. AlphaOne: Reasoning Models Thinking Slow and Fast at Test TimeConference on Empirical Methods in Natural Language Processing (EMNLP)Junyu Zhang, Runpei Dong, Han Wang, et al.2025 · 10 citations
8. MUR: Momentum Uncertainty guided Reasoning for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hang Yan, Fangzhi Xu, Rongman Xu, et al.2026 · 8 citations
9. TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning CompressionarXiv:2506.02678Zhong-Zhi Li, Xiao Liang, Zihao Tang, et al.2025 · 8 citations
10. Mapping the Minds of LLMs: A Graph-Based Analysis of Reasoning LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Xiong, Yujun Cai, Zhecheng Li, et al.2025 · 5 citations
11. Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yongjiang Liu, Haoxi Li, Xiaosong Ma, et al.2026 · 2 citations
12. Correct, Concise and Complete: Multi-stage Training For Adaptive ReasoningFindings of the Association for Computational LinguisticsNathanaël Carraz Rakotonirina, Ren Pang, Neha Anna John, et al.2026 · 1 citation
13. AdaMix: Adaptive Mixing for Short and Long Reasoning AdaptersAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Luo, Xiao Yan, Xinyan Li, et al.2026
14. CLARO: Controlled Attribute-Driven Reasoning Optimization for Efficient Chain-of-ThoughtFindings of the Association for Computational LinguisticsOded Schlesinger, Young Kyung Kim, J. Matias Di Martino, et al.2026

28 more papers of our library cite it; they have no page here yet.

This page in Markdown → https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/cited-by/