---
title: "Who cites M³CoT: A Novel Benchmark for — 30 citing papers"
description: "30 papers of the Elamur Research library cite «M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought», found…"
canonical: "https://research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [M³CoT: A Novel Benchmark for Multi-Domain…](https://md.research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/) / cited by

# Who cites «M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought»

30 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought»](https://md.research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/)

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. **[Vision-Language Models Can Self-Improve Reasoning via Reflection](https://md.research.elamur.ai/free/en/papers/cheng-2025-vision-language-models-can-self/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kanzhi Cheng, Li YanTao, Fangzhi Xu, et al.*2025 · 35 citations*
3. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
4. **[MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification](https://md.research.elamur.ai/free/en/papers/sun-2025-mm-verify-enhancing-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linzhuang Sun, Hao Liang, Jingxuan Wei, et al.*2025 · 19 citations*
5. **[What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices](https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhi Chen, Qiguang Chen, Libo Qin, et al.*2025 · 15 citations*
6. **[Visually-Guided Policy Optimization for Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-visually-guided-policy-optimization-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zengbin Wang, Feng Xiong, Liang Lin, et al.*2026 · 1 citation*
7. [**GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? arXiv:2412.10056**Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lei-2024-gaokao-eval-high-scores/)
8. **[When Seeing Is not Enough: Revealing the Limits of Active Reasoning in MLLMs](https://md.research.elamur.ai/free/en/papers/liu-2026-when-seeing-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongcheng Liu, Pingjie Wang, Yuhao Wang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/) — M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought