Calipper
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sam
Recommendedpaper · 2026-06-09
“Here we present CaliPPer (Calibration and Prediction of Performance), a post-hoc framework pairing a multi-chain Sample-to-Domain Distance (S2DD) with distance-aware Bayesian recalibration, operating at three resolutions: generalisability score, aggregate performance prediction, and per-sample confidence.”
CaliPPer: A Framework for Quantifying and Improving AI Binding Prediction Perfor ↗