DCV-ROOD is a dual cross-validation framework for OOD detection that splits ID data by stratified folds and OOD data by class groups, reproducing benchmark statistical comparisons at lower cost.
In: Pro- ceedings of the 10th Annual Conference on Computational Learning Theory
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DCV-ROOD Evaluation Framework: Dual Cross-Validation for Robust Out-of-Distribution Detection
DCV-ROOD is a dual cross-validation framework for OOD detection that splits ID data by stratified folds and OOD data by class groups, reproducing benchmark statistical comparisons at lower cost.