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license: cc-by-nc-nd-4.0
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---
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license: cc-by-nc-nd-4.0
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task_categories:
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- question-answering
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language:
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- tr
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tags:
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- medical
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pretty_name: d
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size_categories:
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- 1K<n<10K
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paper: https://ieeexplore.ieee.org/abstract/document/10711128
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citation: |
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@inproceedings{incidelen2024developing,
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title={Developing Question-Answering Models in Low-Resource Languages: A Case Study on Turkish Medical Texts Using Transformer-Based Approaches},
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author={{\.I}ncidelen, Mert and Aydo{\u{g}}an, Murat},
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booktitle={2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP)},
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pages={1--4},
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year={2024},
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organization={IEEE}
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}
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---
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