PeFoMed: Parameter Efficient Fine-tuning of Multimodal Large Language Models for Medical Imaging

arXiv:2401.02797v2 Announce Type: replace
Abstract: Multimodal large language models (MLLMs) represent an evolutionary expansion in the capabilities of traditional large language models, enabling them to tackle challenges that surpass the scope of purely text-based applications. It leverages the knowledge previously encoded within these language models, thereby enhancing their applicability and functionality in the reign of multimodal contexts. Recent works investigate the adaptation of MLLMs as a universal solution to address medical multi-modal problems as a generative task. In this paper, …

arxiv cs.ai cs.cl fine-tuning imaging language language models large language large language models medical medical imaging multimodal type