SPIN Unprocessed October 28, 2026 ai_technology research
How Much Fresh Data Should CTR Recalibration Use? A Temporal Evaluation of Post-hoc Calibration
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arXiv:2610.33168v1 Announce Type: new Abstract: Offline evaluation of click-through rate (CTR) models still defaults to random splits, although deployed models score future traffic and downstream systems consume calibrated probabilities. On Avazu (40.4M impressions) we train logistic regression (LR), DeepFM, and DCN-v2 under two rolling temporal origins and a random split, three seeds per arm, and recalibrate each test day with Platt scaling and isotonic regression fitted on the preceding hours.
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