Unleashing the Potential of Large Language Models for Time Series Forecasting

The author proposes a novel framework, LLaTA, to leverage Large Language Models for time series forecasting by bridging the modality gap. By distilling static and dynamic knowledge from LLMs, LLaTA enhances forecasting performance and generalization abilities.