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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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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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+
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+ And here is the paper: [arxiv](arxiv.org/abs/2406.12066)
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+
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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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+ ```