A universal gating framework for multi-expert fusion in heterogeneous multimodal time series forecasting (opens in new tab)

Forecasting future trends in complex systems requires the integration of diverse data sources beyond traditional numerical time series. However, effectively fusing fundamentally heterogeneous data, where external signals, such as textual reports, are independently sourced rather than derived from the series itself, remains a significant challenge. Current multi-modal frameworks often rely on tightly coupled architectures that require complex joint optimization of internal representations, or ...