LDP: Efficient Fine-Tuning of Multimodal LLMs for Medical Report Generation

This research focuses on improving the efficiency of fine-tuning large language models (LLMs) for the specific task of medical report generation, likely leveraging multimodal data. The use of parameter-efficient fine-tuning techniques is crucial in reducing computational costs and resource demands, allowing for more accessible and practical applications in healthcare.

• •Focuses on parameter-efficient fine-tuning, potentially reducing computational costs.
• •Targets medical report generation, implying a healthcare application.
• •Utilizes multimodal LLMs, suggesting the integration of different data modalities (e.g., text, images).