AINeutralarXiv – CS AI · 8h ago6/10
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Divide and Conquer: Object Co-occurrence Helps Mitigate Simplicity Bias in OOD Detection
Researchers propose OCO (Object Co-occurrence), a new out-of-distribution detection framework that leverages object co-occurrence patterns within images to improve the reliability of deep learning models. The method addresses simplicity bias by learning disentangled representations and using divide-and-conquer logic to distinguish near-OOD samples, achieving competitive results across multiple OOD detection benchmarks.