AI RESEARCH
CalArena: A Large-Scale Post-Hoc Calibration Benchmark
arXiv CS.AI
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ArXi:2605.30188v1 Announce Type: cross Reliable probability estimates are critical in many machine learning applications, yet modern classifiers are often poorly calibrated. Post-hoc calibration provides a simple and widely used solution, but the large number of proposed methods, combined with small-scale and inconsistent evaluations, makes it difficult to determine which approaches are truly effective in practice. We