CaliPPer: quantifying, predicting and improving AI model performance for binding prediction

T1Covered by 1 source · first reported by arXiv at 25 Sept, 04:00 UTC

arXiv:2606.07258v1 Announce Type: cross Abstract: Binding prediction models accelerate therapeutic antibody and TCR discovery, but their performance on new datasets is unpredictable, often leading to low discovery rates. Density-ratio methods (PAPE, M-CBPE) provide label-free performance estimation…

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• T1CaliPPer: quantifying, predicting and improving AI model performance for binding predictionarXiv25 Sept, 04:00