AIM-Harvard/rabbit_b4bqa
This is the drug-matching dataset between generic and brand keywords for the RABBIT leaderboard 🐰. And here is the paper: arxiv @misc{gallifant2024language, title={Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks}, 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}, year={2024}, eprint={2406.12066}… See the full description on the dataset page: https://huggingface.co/datasets/AIM-Harvard/rabbit_b4bqa.
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This is the drug-matching dataset between generic and brand keywords for the RABBIT leaderboard 🐰.
And here is the paper: arxiv
@misc{gallifant2024language,
title={Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks},
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},
year={2024},
eprint={2406.12066},
archivePrefix={arXiv},
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.'}
}