---
title: "Who cites Reasoning Models Don't Always Say What They Think"
description: "94 papers of the Elamur Research library cite «Reasoning Models Don't Always Say What They Think», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reasoning Models Don't Always Say What They Think](https://md.research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/) / cited by

# Who cites «Reasoning Models Don't Always Say What They Think»

94 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← back to «Reasoning Models Don't Always Say What They Think»](https://md.research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/)

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. **[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. **[Training Language Models to Reason Efficiently](https://md.research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Daman Arora, Andrea Zanette*2025 · 74 citations*
4. **[Answer Convergence as a Signal for Early Stopping in Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2025-answer-convergence-as-signal-early/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Liu, Lu Wang*2025 · 22 citations*
5. **[Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens](https://md.research.elamur.ai/free/en/papers/zhao-2026-is-chain-thought-reasoning-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengshuai Zhao, Zhen Tan, Pingchuan Ma, et al.*2026 · 21 citations*
6. [**Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models? arXiv:2505.17407**Zhi Rui Tam, Cheng-Kuang Wu, Yu Ying Chiu, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/tam-2025-language-matters-multilingual-input-reasoning/)
7. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations*
8. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
9. **[Is Chain-of-Thought Really Not Explainability? Chain-of-Thought Can Be Faithful without Hint Verbalization](https://md.research.elamur.ai/free/en/papers/zaman-2026-is-chain-thought-really-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kerem Zaman, Shashank Srivastava*2026 · 5 citations*
10. **[Analysing Chain of Thought Dynamics: Active Guidance or Unfaithful Post-hoc Rationalisation?](https://md.research.elamur.ai/free/en/papers/lim-2025-analysing-chain-thought-dynamics-active/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao, et al.*2025 · 5 citations*
11. **[C2-Faith: Benchmarking LLM Judges for Causal and Coverage Faithfulness in Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/mittal-2026-c2-faith-benchmarking-llm-judges/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Avni Mittal, Rauno Arike*2026 · 2 citations*
12. **[Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation](https://md.research.elamur.ai/free/en/papers/zhou-2026-table-question-answering-era-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.*2026 · 2 citations*
13. **[Who Endorsed It? Measuring Authority Bias Across Expertise Levels in Language Models](https://md.research.elamur.ai/free/en/papers/mammen-2026-who-endorsed-it-measuring-authority/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Priyanka Mary Mammen, Emil Joswin, Shankar Venkitachalam*2026 · 1 citation*
14. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
15. **[Choose Your Lens: Multi-Perspective Value Alignment of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhao-2026-choose-your-lens-multi-perspective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gejian Zhao, Hanzhou Wu, Xinpeng Zhang*2026*
16. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*
17. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
18. **[Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains](https://md.research.elamur.ai/free/en/papers/yuan-2026-knowledge-verification-exploring-rlvr-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghang Yuan, Zhefan Wang, Fang Hu, et al.*2026*
19. **[NSF-CoT: Neuro-Symbolic Formal Verification of Chain-of-Thought Faithfulness in Contextual Question Answering](https://md.research.elamur.ai/free/en/papers/pramanik-2026-nsf-cot-neuro-symbolic-formal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vishal Pramanik, Maisha Maliha, Nathaniel D. Bastian, et al.*2026*
20. **[The Inner Monologue of Language Models: When Reasoning Traces Reveal More Than They Hide](https://md.research.elamur.ai/free/en/papers/singla-2026-inner-monologue-language-models-when/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pratham Singla, Shivank Garg, Ayush Singh, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/) — Reasoning Models Don't Always Say What They Think
