Who cites «MANTIS: Interleaved Multi-Image Instruction Tuning»
- LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
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- mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language ModelsarXiv:2408.04840Jiabo Ye, Haiyang Xu, Haowei Liu, et al.2024 · 60 citations
- 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
- InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and OutputarXiv:2407.03320Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.2024 · 39 citations
- Design2Code: Benchmarking Multimodal Code Generation for Automated Front-End EngineeringConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chenglei Si, Yanzhe Zhang, Ryan Li, et al.2025 · 37 citations
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- MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training RecipearXiv:2509.18154Tianyu Yu, Zefan Wang, Chongyi Wang, et al.2025 · 24 citations
- OmniBench: Towards The Future of Universal Omni-Language ModelsConference on Neural Information Processing Systems (NeurIPS)Yizhi Li, Yinghao Ma, Ge Zhang, et al.2024 · 17 citations
- CMM-Math: A Chinese Multimodal Math Dataset To Evaluate and Enhance the Mathematics Reasoning of Large Multimodal ModelsACM International Conference on Multimedia (ACM MM)Wentao Liu, Qianjun Pan, Yi Zhang, et al.2024 · 13 citations
- MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal InteractionarXiv:2604.27393Junbo Cui, Bokai Xu, Chongyi Wang, et al.2026 · 5 citations
- Beyond Single View: A Comprehensive Benchmark for Medical Multimodal Large Language Models on Multi-Image UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Dexuan Xu, Yuan Jiayin, Jianing Wang, et al.2026
- MMTabReal: Real-World Benchmark for Multimodal Table UnderstandingFindings of the Association for Computational LinguisticsPrasham Yatinkumar Titiya, Jainil Trivedi, Chitta Baral, et al.2026
- S2H-DPO: Hardness-Aware Preference Optimization for Vision–Language ModelsFindings of the Association for Computational LinguisticsNitish Shukla, Surgan Jandial, Arun Ross2026
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