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- ---
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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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+ 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:
12
+ - 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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+
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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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+
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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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+ ```