--- title: "Who cites Visual CoT: Advancing — 60 citing papers" description: "60 papers of the Elamur Research library cite «Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and…" canonical: "https://research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Visual CoT: Advancing Multi-Modal Language Models…](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) / cited by # Who cites «Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning» 60 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning»](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) 1. **[LLaVA-CoT: Let Vision Language Models Reason Step-by-Step](https://md.research.elamur.ai/free/en/papers/xu-2024-llava-cot-let-vision-language/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Guowei Xu, Peng Jin, Ziang Wu, et al.*2024 · 138 citations* 2. **[CoT-Valve: Length-Compressible Chain-of-Thought Tuning](https://md.research.elamur.ai/free/en/papers/ma-2025-cot-valve-length-compressible-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyin Ma, Guangnian Wan, Runpeng Yu, et al.*2025 · 64 citations* 3. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations* 4. **[Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xie Zhifei, Mingbao Lin, Zihang Liu, et al.*2025 · 25 citations* 5. **[VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2025-vrag-rl-empower-vision-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Qiuchen Wang, Ruixue Ding, Yu Zeng, et al.*2025 · 23 citations* 6. **[Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-beyond-chain-thought-survey-chain/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yu Xia, Rui Wang, Xu Liu, et al.*2025 · 19 citations* 7. **[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* 8. **[Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset](https://md.research.elamur.ai/free/en/papers/alwajih-2025-pearl-multimodal-culturally-aware-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fakhraddin Alwajih, Samar M. Magdy, Abdellah El Mekki, et al.*2025 · 11 citations* 9. **[SoundMind: RL-Incentivized Logic Reasoning for Audio-Language Models](https://md.research.elamur.ai/free/en/papers/diao-2025-soundmind-rl-incentivized-logic-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xingjian Diao, Chunhui Zhang, Keyi Kong, et al.*2025 · 11 citations* 10. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations* 11. **[ChartAgent: A Multimodal Agent for Visually Grounded Reasoning in Complex Chart Question Answering](https://md.research.elamur.ai/free/en/papers/kaur-2026-chartagent-multimodal-agent-visually-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rachneet Kaur, Nishan Srishankar, Zhen Zeng, et al.*2026 · 5 citations* 12. **[Interleaved Latent Visual Reasoning with Selective Perceptual Modeling](https://md.research.elamur.ai/free/en/papers/dong-2026-interleaved-latent-visual-reasoning-selective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuai Dong, Siyuan Wang, Xingyu Liu, et al.*2026 · 5 citations* 13. **[ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark](https://md.research.elamur.ai/free/en/papers/ghaboura-2026-arb-comprehensive-arabic-multimodal-reasoning/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sara Ghaboura, Shubham Patle, Ketan More, et al.*2026 · 3 citations* 14. **[Forest Before Trees: Latent Superposition for Efficient Visual Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-forest-before-trees-latent-superposition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yubo Wang, Juntian Zhang, Yichen Wu, et al.*2026 · 3 citations* 15. **[Beyond the Panorama: Training-Free Hierarchical Perception-Reasoning for Fine-Grained Vision in MLLMs](https://md.research.elamur.ai/free/en/papers/yi-2026-beyond-panorama-training-free-hierarchical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyang Yi, Jing Chen, Li Peng, et al.*2026* 16. **[GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-govig-goal-conditioned-visual-navigation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fengyi Wu, Yifei Dong, Yilong Dai, et al.*2026* 17. **[Multimodal Large Language Models for Multi-Subject In-Context Image Generation](https://md.research.elamur.ai/free/en/papers/zhou-2026-multimodal-large-language-models-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yucheng Zhou, Dubing Chen, Huan Zheng, et al.*2026* 18. **[SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes](https://md.research.elamur.ai/free/en/papers/wang-2026-scenealign-aligning-multimodal-reasoning-scene/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chuhan Wang, Xintong Li, Jennifer Yuntong Zhang, et al.*2026* 42 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) — Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning