Papers by Mahmoud Salem
MediSwift: Efficient Sparse Pre-trained Biomedical Language Models (2024.findings-acl)
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| Challenge: | Large language models are typically trained on general source data forvarious domains, but domain-specific pre-training is expensive and requires computational costs. |
| Approach: | They propose a suite of biomedicalLMs that leverage sparse pre-training on domain-specific biomedically text data. |
| Outcome: | The proposed model outperforms existing LLMs on biomedical tasks by 22.5x . |