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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.

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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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

bibtex
@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.'}
}