
Smaller, domain-specific models like BioMedLM can compete with larger models in biomedical NLP tasks, offering transparency, privacy, and cost-effectiveness.


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biomedlm-a-2-7-billion-parameter-language-model-trained-exclusively-on-biomedical-text


BioMedLM: A 2.7 Billion Parameter Language Model Trained Exclusively on Biomedical Text


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State-of-the-art large language models are investigated for improving the readability of biomedical abstracts through text simplification.


investigating-large-language-models-and-control-mechanisms-to-improve-text-readability-of-biomedical-abstracts


Investigating Large Language Models and Control Mechanisms to Improve Text Readability of Biomedical Abstracts



Chemical NER models exhibit gender bias, misclassifying female-related names as chemicals, highlighting the need for bias mitigation strategies.


gender-bias-in-chemical-named-entity-recognition-models-study


Gender Bias in Chemical Named Entity Recognition Models Study
