Tag
The paper proposes a Dynamic Fusion Large Language Model (DF-LLM) for traffic flow prediction, integrating spatiotemporal embedding, fusion modules, and an LLM backbone with adaptation strategies to enhance performance over traditional methods in intelligent transportation systems.