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 "id": "huseyincavus/CoTLab_data",
 "owner": "huseyincavus",
 "name": "CoTLab_data",
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 "last_modified": "2026-09-25T09:59:10.000Z",
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 "tasks": [
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 "citation": "@article{jin2021disease,\n  title={What Disease does this Patient Have? A Large-scale Dataset for Medical Knowledge-grounded Dialogue and Question Answering},\n  author={Jin, Di and Pan, Eileen and Oufattole, Nassim and Weng, Wei-Hung and Fang, Hanyi and Szolovits, Peter},\n  journal={Applied Sciences},\n  volume={11},\n  number={4},\n  pages={1696},\n  year={2021},\n  doi={10.3390/app11041696}\n}\n\n@inproceedings{pal2022medmcqa,\n  title={MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering},\n  author={Pal, Ankit and Umapathi, Logesh Kumar and Sankarasubbu, Malaikannan},\n  booktitle={Conference on Health, Inference, and Learning (CHIL)},\n  pages={248--260},\n  year={2022}\n}\n\n@inproceedings{jin2019pubmedqa,\n  title={PubMedQA: A Dataset for Biomedical Research Question Answering},\n  author={Jin, Qiao and Dhingra, Bhuwan and Liu, Zhengping and Cohen, William and Lu, Zhiyong},\n  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP)},\n  pages={2567--2577},\n  year={2019},\n  doi={10.18653/v1/D19-1259}\n}\n\n@inproceedings{hendrycks2021measuring,\n  title={Measuring Massive Multitask Language Understanding},\n  author={Hendrycks, Dan and Burns, Collin and Basart, Steven and Zou, Andy and Mazeika, Mantas and Song, Dawn and Steinhardt, Jacob},\n  booktitle={International Conference on Learning Representations (ICLR)},\n  year={2021}\n}",
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}