Alignment + Accuracy: The Cascade Reward Representation for Preranking
Prerankers in large-scale recommender systems select candidates for a downstream ranker under strict latency constraints. In practice, teams combine accuracy metrics with alignment losses to train and evaluate prerankers, but what these quantities should target—and how to combine them—remains ad hoc. We derive the Casc...