---
title: "Who cites Training Language Models to Reason Efficiently"
description: "72 papers of the Elamur Research library cite «Training Language Models to Reason Efficiently», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Training Language Models to Reason Efficiently](https://md.research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/) / cited by

# Who cites «Training Language Models to Reason Efficiently»

72 papers of our library cite it (of the 149,439 whose bibliographies we read) · 33 with a page here, the most cited first · [← back to «Training Language Models to Reason Efficiently»](https://md.research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/)

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. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
3. [**L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning arXiv:2503.04697**Pranjal Aggarwal, Sean Welleck*2025 · 125 citations*](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-l1-controlling-long-reasoning-model/)
4. [**Dynamic Early Exit in Reasoning Models arXiv:2504.15895**Chenxu Yang, Qingyi Si, Yongjie Duan, et al.*2025 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-dynamic-early-exit-reasoning-models/)
5. [**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/)
6. **[Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching](https://md.research.elamur.ai/free/en/papers/aytes-2025-sketch-thought-efficient-llm-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Simon A. Aytes, Jinheon Baek, Sung Ju Hwang*2025 · 51 citations*
7. **[LightThinker: Thinking Step-by-Step Compression](https://md.research.elamur.ai/free/en/papers/zhang-2025-lightthinker-thinking-step-step-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jintian Zhang, Yuqi Zhu, Mengshu Sun, et al.*2025 · 50 citations*
8. **[AdaptThink: Reasoning Models Can Learn When to Think](https://md.research.elamur.ai/free/en/papers/zhang-2025-adaptthink-reasoning-models-can-learn/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiajie Zhang, Nianyi Lin, Lei Hou, et al.*2025 · 44 citations*
9. [**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/)
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. **[ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/qiao-2025-concise-confidence-guided-compression-step/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziqing Qiao, Yongheng Deng, Jiali Zeng, et al.*2025 · 19 citations*
12. **[AttnPO: Attention-Guided Process Supervision for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/nie-2026-attnpo-attention-guided-process-supervision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuaiyi Nie, Dingsiyu, Wenyuan Zhang, et al.*2026 · 18 citations*
13. **[FoE: Forest of Errors Makes the First Solution the Best in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/jiang-2026-foe-forest-errors-makes-first/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kehan Jiang, Haonan Dong, Zhaolu Kang, et al.*2026 · 15 citations*
14. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations*
15. **[Optimizing Length Compression in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/cheng-2026-optimizing-length-compression-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiang Cheng, Dongping Chen, Mingyang Fu, et al.*2026 · 11 citations*
16. **[Reinforced Efficient Reasoning via Semantically Diverse Exploration](https://md.research.elamur.ai/free/en/papers/zhao-2026-reinforced-efficient-reasoning-semantically-diverse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqi Zhao, Zhaochun Ren, Jiahong Zou, et al.*2026 · 9 citations*
17. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
18. **[Do LLMs Really Need 10+ Thoughts for “Find the Time 1000 Days Later”? Towards Structural Understanding of LLM Overthinking](https://md.research.elamur.ai/free/en/papers/zhang-2026-do-llms-really-need-10/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinliang Frederick Zhang, Anhad Mohananey, Alexandra Chronopoulou, et al.*2026 · 4 citations*
19. **[DeepPrune: Parallel Scaling without Inter-trace Redundancy](https://md.research.elamur.ai/free/en/papers/tu-2026-deepprune-parallel-scaling-without-inter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shangqing Tu, Yaxuan Li, Yushi Bai, et al.*2026 · 3 citations*
20. **[REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once](https://md.research.elamur.ai/free/en/papers/pan-2026-rest-stress-testing-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuoshi Pan, Qizhi Pei, Yu Li, et al.*2026 · 3 citations*
21. **[Beyond Token Length: Step Pruner for Efficient and Accurate Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-token-length-step-pruner/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Canhui Wu, Qiong Cao, Chang Li, et al.*2026 · 2 citations*
22. **[Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-think-how-think-mitigating-overthinking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongjiang Liu, Haoxi Li, Xiaosong Ma, et al.*2026 · 2 citations*
23. **[Graph-Based Chain-of-Thought Pruning for Reducing Redundant Reflections in Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/yuan-2026-graph-based-chain-thought-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongyuan Yuan, Xinran He, Run Shao, et al.*2026 · 1 citation*
24. **[Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-listen-pause-reason-perception-grounded/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jieyi Wang, Yazhe Niu, Dexuan Xu, et al.*2026 · 1 citation*
25. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanbing Liu, Lang Cao, Yuanyi Ren, et al.*2026 · 1 citation*
26. **[When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/xiang-2026-when-is-thinking-enough-early/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xiang, Yixin Ji, Ruotao Xu, et al.*2026 · 1 citation*
27. **[AdaMix: Adaptive Mixing for Short and Long Reasoning Adapters](https://md.research.elamur.ai/free/en/papers/luo-2026-adamix-adaptive-mixing-short-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Luo, Xiao Yan, Xinyan Li, et al.*2026*
28. **[CLARO: Controlled Attribute-Driven Reasoning Optimization for Efficient Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/schlesinger-2026-claro-controlled-attribute-driven-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oded Schlesinger, Young Kyung Kim, J. Matias Di Martino, et al.*2026*
29. **[Exploration-Exploitation Reshaping towards Efficient Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-exploration-exploitation-reshaping-efficient-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufeng Shi, Weilin Luo, Yuxiang Zhang, et al.*2026*
30. **[Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting](https://md.research.elamur.ai/free/en/papers/xia-2026-merlin-s-whisper-enabling-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Heming Xia, Cunxiao Du, Rui Li, et al.*2026*
31. **[Shorten After You're Right: Lazy Length Penalties for Reasoning RL](https://md.research.elamur.ai/free/en/papers/yuan-2026-shorten-after-you-re-right/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Danlong Yuan, Tian Xie, Shaohan Huang, et al.*2026*
32. **[Stabilizing Efficient Reasoning with Step-Level Advantage Selection](https://md.research.elamur.ai/free/en/papers/wang-2026-stabilizing-efficient-reasoning-step-level/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Wang, Xiaodong Yu, Jialian Wu, et al.*2026*
33. **[Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/sheng-2026-think-smart-not-hard-difficulty/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Sheng, Shilin Zhou, Chen Gong, et al.*2026*

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

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