Auditing Regime-Stratified Evaluation for Time-Series Foundation Models
Developed a pre-registered self-audit framework for regime-stratified evaluation of time-series foundation models on traffic forecasting. The project uses meaning-destroying but structure-preserving null controls, label-family sensitivity analysis, cross-dataset checks, and interval-calibration diagnostics to test whether a reported conditional failure is genuinely attributable to the named regime. It reframes a refuted headline as four measurable preconditions for trustworthy stratified evaluation.