--- title: "Who cites Enhancing the Reasoning Ability — 40 citing papers" description: "40 papers of the Elamur Research library cite «Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference…" canonical: "https://research.elamur.ai/free/en/papers/wang-2024-enhancing-reasoning-ability-multimodal-large/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2024-enhancing-reasoning-ability-multimodal-large/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Enhancing the Reasoning Ability of Multimodal…](https://md.research.elamur.ai/free/en/papers/wang-2024-enhancing-reasoning-ability-multimodal-large/) / cited by # Who cites «Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization» 40 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization»](https://md.research.elamur.ai/free/en/papers/wang-2024-enhancing-reasoning-ability-multimodal-large/) 1. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/) 2. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/) 3. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/) 4. **[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* 5. [**Intern-S1: A Scientific Multimodal Foundation Model arXiv:2508.15763**Lei Bai, Zhongrui Cai, Yuhang Cao, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-intern-s1-scientific-multimodal/) 6. [**Skywork R1V2: Multimodal Hybrid Reinforcement Learning for Reasoning arXiv:2504.16656**Peiyu Wang, Yichen Wei, Yi Peng, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-skywork-r1v2-multimodal-hybrid/) 7. **[DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture](https://md.research.elamur.ai/free/en/papers/maji-2025-drishtikon-multimodal-multilingual-benchmark-testing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Arijit Maji, Raghvendra Kumar, Akash Ghosh, et al.*2025 · 9 citations* 8. **[DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal Reasoning](https://md.research.elamur.ai/free/en/papers/sivakumaran-2026-dart-leveraging-multi-agent-disagreement/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Nithin Sivakumaran, Justin Chen, David Wan, et al.*2026 · 1 citation* 9. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyue Lou, Xu Jinan, Jingyi Yin, et al.*2026 · 1 citation* 10. **[CoreGaze: Core Subgraph-Driven Visual Gaze Diffusion for Training-Free Referring Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/yi-2026-coregaze-core-subgraph-driven-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyang Yi, Jing Chen, Yuru Bao, et al.*2026* 11. **[FAER: Benchmarking VLMs for Failure-Aware Embodied Reasoning](https://md.research.elamur.ai/free/en/papers/song-2026-faer-benchmarking-vlms-failure-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Song, Kaifeng Liu, Yuanxing Liu, et al.*2026* 12. **[MobileBench-OL: A Comprehensive Chinese Benchmark for Evaluating Mobile GUI Agents in Real-World Environment](https://md.research.elamur.ai/free/en/papers/wu-2026-mobilebench-ol-comprehensive-chinese-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qinzhuo Wu, Zhizhuo Yang, Hanhao Li, et al.*2026* 13. **[MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems](https://md.research.elamur.ai/free/en/papers/yuksel-2026-moneta-multimodal-industry-classification-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arda Yüksel, Gabriel Thiem, Susanne Walter, et al.*2026* 27 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2024-enhancing-reasoning-ability-multimodal-large/) — Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization