🔗 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) · 10 with a page here, the most cited first · ← back to «Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization»

1. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
2. InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal ModelsarXiv:2504.10479Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.2025 · 216 citations
3. InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
4. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
5. Intern-S1: A Scientific Multimodal Foundation ModelarXiv:2508.15763Lei Bai, Zhongrui Cai, Yuhang Cao, et al.2025 · 19 citations
6. Skywork R1V2: Multimodal Hybrid Reinforcement Learning for ReasoningarXiv:2504.16656Peiyu Wang, Yichen Wei, Yi Peng, et al.2025 · 10 citations
7. DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian CultureConference on Empirical Methods in Natural Language Processing (EMNLP)Arijit Maji, Raghvendra Kumar, Akash Ghosh, et al.2025 · 9 citations
8. DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal ReasoningConference of the European Chapter of the Association for Computational Linguistics (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 LifeFindings of the Association for Computational LinguisticsXinyue Lou, Xu Jinan, Jingyi Yin, et al.2026 · 1 citation
10. FAER: Benchmarking VLMs for Failure-Aware Embodied ReasoningFindings of the Association for Computational LinguisticsHao Song, Kaifeng Liu, Yuanxing Liu, et al.2026

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

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