model-cascade

UCCI proposes a calibration-first router for LLM cascades that uses isotonic regression to map token-level margin uncertainty to error probability, achieving a 31% cost reduction on a production NER workload while maintaining micro-F1=0.91 and reducing expected calibration error from 0.12 to 0.03.