Calibration-Aware Uncertainty Cascades for Efficient Heterogeneous Model Collaboration

Heterogeneous model collaboration seeks to exploit the complementary strengths of different models to balance predictive performance and inference cost. Existing approaches typically rely either on trained routers, which tie routing decisions to a fixed task and model pool, or on raw-confidence casc