Chen-Xiang Li

Fine-tuned large language models enhance influenza forecasting.

A lightweight fine-tuning framework is developed that adapts pre-trained LLMs using compact embedding and prediction layers and evaluates it on seven weekly aggregated real-world surveillance datasets, establishing fine-tuned LLMs as efficient and robust forecasting tools suitable for privacy-sensitive, data-scarce pub...