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@@ -22,6 +22,10 @@ Pretraining dataset aligned with [GIFT-Eval](https://huggingface.co/datasets/Sal
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  [🏎️ Leader Board](https://huggingface.co/spaces/Salesforce/GIFT-Eval)
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  ## Citation
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  <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
@@ -34,4 +38,4 @@ If you find this benchmark useful, please consider citing:
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  author={Taha Aksu and Gerald Woo and Juncheng Liu and Xu Liu and Chenghao Liu and Silvio Savarese and Caiming Xiong and Doyen Sahoo},
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  journal = {arxiv preprint arxiv:2410.10393},
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  year={2024},
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- ```
 
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  [🏎️ Leader Board](https://huggingface.co/spaces/Salesforce/GIFT-Eval)
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+ ## Ethical Considerations
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+ This release is for research purposes only in support of an academic paper. Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes. We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model. We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting use cases, particularly for high-risk scenarios where errors or misuse could significantly impact people’s lives, rights, or safety. For further guidance on use cases, refer to our AUP and AI AUP.
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+
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  ## Citation
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  <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
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  author={Taha Aksu and Gerald Woo and Juncheng Liu and Xu Liu and Chenghao Liu and Silvio Savarese and Caiming Xiong and Doyen Sahoo},
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  journal = {arxiv preprint arxiv:2410.10393},
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  year={2024},
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+ ```