ScoringBench: A Benchmark for Evaluating Tabular Foundation Models with Proper Scoring Rules
By: Jonas Landsgesell, Pascal Knoll
Published: 2026-04-01
View on arXiv →#cs.AI
Abstract
ScoringBench is introduced as a benchmark for evaluating tabular foundation models using proper scoring rules. This is crucial for assessing the reliability and calibration of predictions from these models, which are widely used in various real-world applications such as finance, healthcare, and recommendation systems.