arXiv Open Access 2025

SOLVE-Med: Specialized Orchestration for Leading Vertical Experts across Medical Specialties

Roberta Di Marino Giovanni Dioguardi Antonio Romano Giuseppe Riccio Mariano Barone +3 lainnya
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Abstrak

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.

Topik & Kata Kunci

Penulis (8)

R

Roberta Di Marino

G

Giovanni Dioguardi

A

Antonio Romano

G

Giuseppe Riccio

M

Mariano Barone

M

Marco Postiglione

F

Flora Amato

V

Vincenzo Moscato

Format Sitasi

Marino, R.D., Dioguardi, G., Romano, A., Riccio, G., Barone, M., Postiglione, M. et al. (2025). SOLVE-Med: Specialized Orchestration for Leading Vertical Experts across Medical Specialties. https://arxiv.org/abs/2511.03542

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓