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--- |
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language: |
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- it |
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--- |
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This is a machine-translated version of [The Cauldron](https://huggingface.co./datasets/HuggingFaceM4/the_cauldron) for the Italian language. |
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Out of the 50 tasks, only a subset of 15 tasks which do not lose their meaning after machine translation are considered (specifically, tasks which focus on the textual contents of images are removed). |
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Out of these 15 tasks, the first 10k rows are selected for machine translation. Question-Answer pairs that were not correctly translated were discarded. |
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Image paths are formatted using the following strategy: |
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``` |
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{task-name}/images/{row_number}_{image_number} |
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``` |
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Where {task-name} is the name of the task from the original dataset, {row_number} is the row number in the original dataset and {image_number} the index of the image (in case of tasks where there can be multiple images as input). |
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## Citation |
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If you use this dataset in your research please cite the following |
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``` |
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@inproceedings{musacchioLLaVANDiNO, |
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title={LLaVA-NDiNO: Empowering LLMs with Multimodality for the Italian Language}, |
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author={Musacchio, Elio and Siciliani, Lucia and Basile, Pierpaolo and Semeraro, Giovanni}, |
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booktitle={Proceedings of the Eighth Workshop on Natural Language for Artificial Intelligence (NL4AI 2024) co-located with 23th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2024)}, |
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year={2024} |
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} |
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@misc{laurençon2024matters, |
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title={What matters when building vision-language models?}, |
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author={Hugo Laurençon and Léo Tronchon and Matthieu Cord and Victor Sanh}, |
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year={2024}, |
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eprint={2405.02246}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV} |
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} |
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``` |
