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  * [2024.05.28] πŸ“ƒ Our RLAIF-V paper is accesible at [arxiv](https://arxiv.org/abs/2405.17220) now!
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  * [2024.05.20] πŸŽ‰ We introduce [RLAIF-V](https://github.com/RLHF-V/RLAIF-V), our new alignment framework that utilize open-source models for feedback generation and reach **super GPT-4V trustworthiness**. You can download the corresponding [dataset](https://huggingface.co/datasets/openbmb/RLAIF-V-Dataset) and models ([7B](https://huggingface.co/openbmb/RLAIF-V-7B), [12B](https://huggingface.co/openbmb/RLAIF-V-12B)) now!
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- * [2024.04.11] πŸ”₯ Our data is used in [MiniCPM-V 2.0](https://huggingface.co/openbmb/MiniCPM-V-2), an **end-side** multimodal large language model that exhibits **comparable trustworthiness with GPT-4V**!
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  * [2024.05.28] πŸ“ƒ Our RLAIF-V paper is accesible at [arxiv](https://arxiv.org/abs/2405.17220) now!
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  * [2024.05.20] πŸŽ‰ We introduce [RLAIF-V](https://github.com/RLHF-V/RLAIF-V), our new alignment framework that utilize open-source models for feedback generation and reach **super GPT-4V trustworthiness**. You can download the corresponding [dataset](https://huggingface.co/datasets/openbmb/RLAIF-V-Dataset) and models ([7B](https://huggingface.co/openbmb/RLAIF-V-7B), [12B](https://huggingface.co/openbmb/RLAIF-V-12B)) now!
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+ * [2024.04.11] πŸ”₯ Our data is used in [MiniCPM-V 2.0](https://huggingface.co/openbmb/MiniCPM-V-2), an **end-side** multimodal large language model that exhibits **comparable trustworthiness with GPT-4V**!
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+ ## Citation
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+ If you find this dataset helpful, please consider cite our papers πŸ“:
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+ ```
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+ @article{yu2023rlhf,
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+ title={Rlhf-v: Towards trustworthy mllms via behavior alignment from fine-grained correctional human feedback},
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+ author={Yu, Tianyu and Yao, Yuan and Zhang, Haoye and He, Taiwen and Han, Yifeng and Cui, Ganqu and Hu, Jinyi and Liu, Zhiyuan and Zheng, Hai-Tao and Sun, Maosong and others},
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+ journal={arXiv preprint arXiv:2312.00849},
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+ year={2023}
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+ }
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+
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+ @article{yu2024rlaifv,
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+ title={RLAIF-V: Aligning MLLMs through Open-Source AI Feedback for Super GPT-4V Trustworthiness},
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+ author={Tianyu Yu and Haoye Zhang and Yuan Yao and Yunkai Dang and Da Chen and Xiaoman Lu and Ganqu Cui and Taiwen He and Zhiyuan Liu and Tat-Seng Chua and Maosong Sun},
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+ journal={arXiv preprint arXiv:2405.17220},
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+ year={2024},
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+ }
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+ ```