SOLVE-Med: Specialized Orchestration for Leading Vertical Experts across Medical Specialties
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Abstract (arXiv)
Medical question answering systems face deployment challenges including hallucinations, bias, computational demands, privacy concerns, and the need for specialized expertise across diverse domains. Here, we present SOLVE-Med, a multi-agent architecture combining domain-specialized small language models for complex medical queries. The system employs a Router Agent for dynamic specialist selection, ten specialized models (1B parameters each) fine-tuned on specific medical domains, and an Orchestrator Agent that synthesizes responses. Evaluated on Italian medical forum data across ten specialties, SOLVE-Med achieves superior performance with ROUGE-1 of 0.301 and BERTScore F1 of 0.697, outperforming standalone models up to 14B parameters while enabling local deployment. Our code is publicly available on GitHub: https://github.com/PRAISELab-PicusLab/SOLVE-Med.
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References · 13
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
- 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
- 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,243
- 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,841
- 2024Large Language Model based Multi-Agents: A Survey of Progress and Challengescited by 752
- 2023Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessmentcited by 227
- 2023Large language models in healthcare and medical domain: A reviewcited by 126
- 2024A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthinesscited by 125
- 2024What is the Role of Small Models in the LLM Era: A Surveycited by 41
- 2024Large Language Models for Medicine: A Surveycited by 38
- 2024LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Modelscited by 31
- 2024Small Language Models Learn Enhanced Reasoning Skills from Medical Textbookscited by 30
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