DG-LLM: Decomposition-based dynamic graph adaptation of large language models for spatiotemporal traffic forecasting
Fig 5
Statistical significance of DG-LLM improvements.
Heatmaps show percentage reduction in MAE and RMSE relative to baseline models (n = 5 seeds), along with corresponding significance levels. Colors denote significance: purple (p < 0.001), red (p < 0.01), orange (p < 0.05), and grey (not significant). Upward arrows (↑) indicate error reduction by DG-LLM.