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--- |
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license: apache-2.0 |
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task_categories: |
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- question-answering |
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language: |
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- en |
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tags: |
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- medical |
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--- |
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This is the drug-matching dataset between generic and brand keywords for the RABBIT leaderboard [🐰](https://huggingface.co/spaces/AIM-Harvard/rabbits-leaderboard). |
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And here is the paper: [arxiv](arxiv.org/abs/2406.12066) |
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```bibtex |
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@misc{gallifant2024language, |
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title={Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks}, |
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author={Jack Gallifant and Shan Chen and Pedro Moreira and Nikolaj Munch and Mingye Gao and Jackson Pond and Leo Anthony Celi and Hugo Aerts and Thomas Hartvigsen and Danielle Bitterman}, |
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year={2024}, |
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eprint={2406.12066}, |
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archivePrefix={arXiv}, |
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primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'} |
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} |
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``` |
