Blaise Genest

Adaptive Multi-prompt Contrastive Network for Few-shot Out-of-distribution Detection

Out-of-distribution (OOD) detection attempts to distinguish outlier samples to prevent models trained on the in-distribution (ID) dataset from producing unavailable outputs. Most OOD detection methods require many ID samples for training, which seriously limits their real-world applications. To this…