🔗 Who cites «MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark»

120 papers of our library cite it (of the 149,439 whose bibliographies we read) · 39 with a page here, the most cited first · ← back to «MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark»

1. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 1,031 citations
2. Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any ResolutionarXiv:2409.12191Peng Wang, Shuai Bai, Sinan Tan, et al.2024 · 860 citations
3. Qwen3-VL Technical ReportarXiv:2511.21631Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.2025 · 370 citations
4. 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
5. Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations
6. SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-trainingarXiv:2501.17161Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.2025 · 160 citations
7. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
8. Qwen3-Omni Technical ReportarXiv:2509.17765Jin Xu, Zhifang Guo, Hangrui Hu, et al.2025 · 117 citations
9. GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement LearningarXiv:2507.01006GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.2025 · 89 citations
10. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
11. Kimi K2.5: Visual Agentic IntelligencearXiv:2602.02276Kimi Team, Tongtong Bai, Yifan Bai, et al.2026 · 66 citations
12. MedXpertQA: Benchmarking Expert-Level Medical Reasoning and UnderstandingarXiv:2501.18362Yuxin Zuo, Shang Qu, Yifei Li, et al.2025 · 65 citations
13. MiniMax-01: Scaling Foundation Models with Lightning AttentionarXiv:2501.08313MiniMax, Aonian Li, Bangwei Gong, et al.2025 · 50 citations
14. MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at ScaleAnnual Meeting of the Association for Computational Linguistics (ACL)Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.2025 · 40 citations
15. MiMo-VL Technical ReportarXiv:2506.03569Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.2025 · 33 citations
16. Qwen3.5-Omni Technical ReportarXiv:2604.15804Qwen Team2026 · 29 citations
17. ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error DetectionFindings of the Association for Computational LinguisticsYibo Yan, Shen Wang, Jiahao Huo, et al.2026 · 23 citations
18. CAMEL-Bench: A Comprehensive Arabic LMM BenchmarkFindings of the Association for Computational LinguisticsSara Ghaboura, Ahmed Heakl, Omkar Thawakar, et al.2025 · 22 citations
19. MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific UnderstandingarXiv:2407.04903Zekun Li, Xianjun Yang, Kyuri Choi, et al.2024 · 20 citations
20. SciVer: Evaluating Foundation Models for Multimodal Scientific Claim VerificationAnnual Meeting of the Association for Computational Linguistics (ACL)Chengye Wang, Yifei Shen, Zexi Kuang, et al.2025 · 11 citations
21. Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2025 · 11 citations
22. Skywork R1V2: Multimodal Hybrid Reinforcement Learning for ReasoningarXiv:2504.16656Peiyu Wang, Yichen Wei, Yi Peng, et al.2025 · 10 citations
23. ViLBench: A Suite for Vision-Language Process Reward ModelingConference on Empirical Methods in Natural Language Processing (EMNLP)Haoqin Tu, Weitao Feng, Hardy Chen, et al.2025 · 9 citations
24. ERNIE 5.0 Technical ReportarXiv:2602.04705Haifeng Wang, Hua Wu, Tian Wu, et al.2026 · 7 citations
25. Skywork-R1V3 Technical ReportarXiv:2507.06167Wei Shen, Jiangbo Pei, Yi Peng, et al.2025 · 6 citations
26. DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache CompressionarXiv:2609.19969DeepSeek-AI, Anyi Xu, B. Li, et al.2026 · 3 citations
27. Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion ScalearXiv:2603.25040Yicheng Zou, Dongsheng Zhu, Lin Zhu, et al.2026 · 3 citations
28. VLM@school — Evaluation of AI image understanding on German middle school knowledgeLecture notes in networks and systemsRene Peinl, Vincent Tischler2025 · 3 citations
29. Visually-Guided Policy Optimization for Multimodal ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Zengbin Wang, Feng Xiong, Liang Lin, et al.2026 · 1 citation
30. Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning ModelsFindings of the Association for Computational LinguisticsHoang Phan, Xianjun Yang, Yuanshun Yao, et al.2026
31. Evaluating Discriminability of Vision-Language ModelsLanguage Resources and Evaluation Conference (LREC)Masayasu Muraoka, Naoaki Okazaki2026
32. Multimodal LLMs Do Not Compose Skills Optimally across ModalitiesLanguage Resources and Evaluation Conference (LREC)Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune2026
33. Omni-I2C: A Holistic Benchmark for High-Fidelity Image-to-Code GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Jiawei Zhou, Chi Zhang, Xiang Feng, et al.2026
34. Seeing Beyond Words: MatVQA for Challenging Visual-Scientific Reasoning in Materials ScienceFindings of the Association for Computational LinguisticsSifan Wu, Huan Zhang, Yizhan Li, et al.2026
35. Seeing the Other Side: Diagnostic Tasks for Viewpoint Reasoning in Vision–Language ModelsLanguage Resources and Evaluation Conference (LREC)Makoto Takenaka, Hitomi Yanaka2026
36. Thesis Proposal: Multimodal Benchmark for Music Understanding in Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Tomáš Sourada2026
37. VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Wenyi Xiao, Xinchi XU, Leilei Gan2026
38. Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine TranslationAnnual Conference of the European Association for Machine Translation (EAMT)Shenbin Qian, Yves Scherrer2026
39. Your Reasoning Benchmark May Not Test Reasoning: Revealing Perception Bottleneck in Abstract Reasoning BenchmarksAnnual Meeting of the Association for Computational Linguistics (ACL)Xinhe Wang, Jin Huang, Xingjian Zhang, et al.2026

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