A frozen-LLM framework with dual-branch token alignment and spatio-temporal prompts beats prior epidemic forecasting models on four COVID-19 datasets.
Why is it difficult to accurately predict the covid-19 epidemic? Infectious disease modelling, 5:271–281, 2020
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EpiLLM: Unlocking the Potential of Large Language Models in Epidemic Forecasting
A frozen-LLM framework with dual-branch token alignment and spatio-temporal prompts beats prior epidemic forecasting models on four COVID-19 datasets.