---
title: "Who cites Can Large Language Models — 26 citing papers"
description: "26 papers of the Elamur Research library cite «Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?», found in their…"
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---
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# Who cites «Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?»

26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?»](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/)

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. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
3. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
4. **[What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/jiang-2025-what-makes-good-reasoning-chain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gangwei Jiang, Yahui Liu, Zhaoyi Li, et al.*2025 · 11 citations*
5. **[M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation](https://md.research.elamur.ai/free/en/papers/liu-2025-m2rc-eval-massively-multilingual-repository/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaheng Liu, Ken Deng, Congnan Liu, et al.*2025 · 8 citations*
6. **[DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation](https://md.research.elamur.ai/free/en/papers/zheng-2026-deeppresenter-environment-grounded-reflection-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zheng, Guozhao Mo, Xinru Yan, et al.*2026 · 3 citations*
7. **[Beyond Meta-Reasoning: Metacognitive Consolidation for Self-Improving LLM Reasoning](https://md.research.elamur.ai/free/en/papers/zhuang-2026-beyond-meta-reasoning-metacognitive-consolidation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqing Zhuang, Linhai Zhang, Jiasheng Si, et al.*2026 · 1 citation*
8. **[RAFFLES: Reasoning-based Attribution of Faults for LLM Systems](https://md.research.elamur.ai/free/en/papers/zhu-2026-raffles-reasoning-based-attribution-faults/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chenyang Zhu, Spencer Hong, Jingyu Wu, et al.*2026 · 1 citation*
9. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) — Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?