--- title: "Who cites GIT: A Generative Image-to-text — 114 citing papers" description: "114 papers of the Elamur Research library cite «GIT: A Generative Image-to-text Transformer for Vision and Language», found in their…" canonical: "https://research.elamur.ai/free/en/papers/wang-2022-git-generative-image-text-transformer/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2022-git-generative-image-text-transformer/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [GIT: A Generative Image-to-text Transformer for…](https://md.research.elamur.ai/free/en/papers/wang-2022-git-generative-image-text-transformer/) / cited by # Who cites «GIT: A Generative Image-to-text Transformer for Vision and Language» 114 papers of our library cite it (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · [← back to «GIT: A Generative Image-to-text Transformer for Vision and Language»](https://md.research.elamur.ai/free/en/papers/wang-2022-git-generative-image-text-transformer/) 1. [**Visual Instruction Tuning arXiv:2304.08485**Haotian Liu, Chunyuan Li, Qingyang Wu, et al.*2023 · 2,617 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-visual-instruction-tuning/) 2. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning arXiv:2305.06500**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,100 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/) 3. **[MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 554 citations* 4. **[CogVLM: Visual Expert for Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.*2023 · 383 citations* 5. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model arXiv:2209.06794**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 371 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/) 6. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/) 7. **[HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 335 citations* 8. **[Language Is Not All You Need: Aligning Perception with Language Models](https://md.research.elamur.ai/free/en/papers/huang-2023-language-all-need-aligning-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shaohan Huang, Li Dong, Wenhui Wang, et al.*2023 · 330 citations* 9. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/) 10. **[OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 306 citations* 11. **[TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering](https://md.research.elamur.ai/free/en/papers/hu-2023-tifa-accurate-interpretable-text-image/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Yushi Hu, Benlin Liu, Jungo Kasai, et al.*2023 · 218 citations* 12. [**Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic arXiv:2306.15195**Keqin Chen, Zhao Zhang, Weili Zeng, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-shikra-unleashing-multimodal-llm-s/) 13. [**NExT-GPT: Any-to-Any Multimodal LLM arXiv:2309.05519**Shengqiong Wu, Hao Fei, Leigang Qu, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-next-gpt-any-any-multimodal/) 14. [**MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action arXiv:2303.11381**Zhengyuan Yang, Linjie Li, Jianfeng Wang, et al.*2023 · 196 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-mm-react-prompting-chatgpt-multimodal/) 15. [**Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning arXiv:2306.14565**Fuxiao Liu, Kevin Lin, Linjie Li, et al.*2023 · 189 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mitigating-hallucination-large-multi-modal/) 16. [**Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding arXiv:2210.03347**Kenton Lee, Mandar Joshi, Iulia Turc, et al.*2022 · 158 citations*](https://md.research.elamur.ai/free/en/papers/lee-2022-pix2struct-screenshot-parsing-pretraining-visual/) 17. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/) 18. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/) 19. **[Violet: A Vision-Language Model for Arabic Image Captioning with Gemini Decoder](https://md.research.elamur.ai/free/en/papers/mohamed-2023-violet-vision-language-model-arabic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Abdelrahman Mohamed, Fakhraddin Alwajih, El Moatez Billah Nagoudi, et al.*2023 · 18 citations* 20. **[Text-Guided Multi-Scale Frequency Representation Adaptation](https://md.research.elamur.ai/free/en/papers/yan-2026-text-guided-multi-scale-frequency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weicai Yan, Xinhua Ma, Wang Lin, et al.*2026* 94 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2022-git-generative-image-text-transformer/) — GIT: A Generative Image-to-text Transformer for Vision and Language