|
--- |
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license: cc-by-nc-4.0 |
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dataset_info: |
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features: |
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- name: text |
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list: |
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- name: content |
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dtype: string |
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- name: role |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 3946452 |
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num_examples: 3067 |
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download_size: 1687475 |
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dataset_size: 3946452 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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|
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# HerO at AVeriTeC |
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**[Paper](https://arxiv.org/abs/2410.12377) | [Code](https://github.com/ssu-humane/HerO)** |
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## Summaries |
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This is the modified instruction-tuning dataset derived from the [AVeriTeC dataset](https://huggingface.co/chenxwh/AVeriTeC), designed for fine-tuning large language models to predict verdicts and justifications in fact-checking tasks within AVeriTeC. |
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|
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## License |
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This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License, following the original [AVeriTeC dataset](https://huggingface.co/chenxwh/AVeriTeC) license." |
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## Citation |
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``` |
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@article{yoon2024hero, |
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title={HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims}, |
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author={Yoon, Yejun and Jung, Jaeyoon and Yoon, Seunghyun and Park, Kunwoo}, |
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journal={arXiv preprint arXiv:2410.12377}, |
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year={2024} |
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} |
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``` |
