Visual edits lose their grip mid-decoder: equal-strength interventions fade before answers settle, and calibrated routing turns that into attribute accuracy
Applying the same visual-residual edit at every decoder layer with matched RMS strength reveals a persistent drop in effect, called the Evidence Anchoring Boundary; routing interventions by question type and calibration improves full-set attribute accuracy across three checkpoints, while universal subtraction is neutral or harmful.