🔗 Who cites «ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models»

56 papers of our library cite it (of the 141,840 whose bibliographies we read) · 9 with a page here, the most cited first · ← back to «ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models»

1. Qwen2.5-VL Technical ReportarXiv:2502.13923Shuai Bai, Keqin Chen, Xuejing Liu, et al.2025 · 948 citations
   How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source SuitesScience China Information SciencesZhe Chen, Weiyun Wang, Hao Tian, et al.2024 · 529 citations
   Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 517 citations
2. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 440 citations
3. 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 · 276 citations
4. MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 267 citations
   Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 184 citations
   Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 173 citations
5. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 135 citations

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

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