AlpaCare:Instruction-tuned Large Language Models for Medical Application

arXiv:2310.14558v2 Announce Type: replace
Abstract: Instruction-finetuning (IFT) has become crucial in aligning Large Language Models (LLMs) with diverse human needs and has shown great potential in medical applications. However, previous studies mainly fine-tune LLMs on biomedical datasets with limited diversity, which often rely on benchmarks or narrow task scopes, and hence significantly limit the effectiveness on their medical instruction-following ability and generalizability. To bridge this gap, we propose creating a diverse, machine-generated medical IFT dataset, MedInstruct-52k, using GPT-4 and ChatGPT …

application arxiv cs.ai cs.cl instruction-tuned language language models large language large language models medical type