The author proposes SERVAL, a synergy learning pipeline that enhances zero-shot medical prediction by leveraging the knowledge of large language models and small vertical models through mutual enhancement.
SERVAL proposes a synergy learning pipeline to enhance the vertical capabilities of large language models (LLMs) and small models through mutual enhancement, achieving competitive performance in medical prediction without gold labels.