All datasets / huseyincavus
huseyincavus/CoTLab_data
The declared licence (cc-by-nc-sa-4.0) is classified as having use restrictions.
- Declared licence
- cc-by-nc-sa-4.0, from the tagEvidence: README.md at 0b09468
- Licence files
- No licence file at the top level of the repositoryEvidence: file list at 0b09468
- Declared sources
- None listed in the card metadata
- Access gated on Hugging Face
- No
Tasks
Citation text from the card
@article{jin2021disease,
title={What Disease does this Patient Have? A Large-scale Dataset for Medical Knowledge-grounded Dialogue and Question Answering},
author={Jin, Di and Pan, Eileen and Oufattole, Nassim and Weng, Wei-Hung and Fang, Hanyi and Szolovits, Peter},
journal={Applied Sciences},
volume={11},
number={4},
pages={1696},
year={2021},
doi={10.3390/app11041696}
}
@inproceedings{pal2022medmcqa,
title={MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering},
author={Pal, Ankit and Umapathi, Logesh Kumar and Sankarasubbu, Malaikannan},
booktitle={Conference on Health, Inference, and Learning (CHIL)},
pages={248--260},
year={2022}
}
@inproceedings{jin2019pubmedqa,
title={PubMedQA: A Dataset for Biomedical Research Question Answering},
author={Jin, Qiao and Dhingra, Bhuwan and Liu, Zhengping and Cohen, William and Lu, Zhiyong},
booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
pages={2567--2577},
year={2019},
doi={10.18653/v1/D19-1259}
}
@inproceedings{hendrycks2021measuring,
title={Measuring Massive Multitask Language Understanding},
author={Hendrycks, Dan and Burns, Collin and Basart, Steven and Zou, Andy and Mazeika, Mantas and Song, Dawn and Steinhardt, Jacob},
booktitle={International Conference on Learning Representations (ICLR)},
year={2021}
}
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dataset_licence({ "id": "huseyincavus/CoTLab_data" })
signal: "restrictive"
stated_licence: "cc-by-nc-sa-4.0"
sources: 0