EvoCast: Reliable Autonomous Research Agents for Iterative Forecasting Architecture Evolution

Deep time-series forecasting models have rapidly diversified, yet adapting them to a specific task still requires extensive expert effort in model selection, mechanism diagnosis, architecture design, implementation, and evaluation. Existing AutoML methods are constrained by predefined search spaces,