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Recent Advances in OOD Detection: Problems and Approaches
S Lu, Y Wang, L Sheng, A Zheng, L He… - arxiv preprint arxiv …, 2024 - arxiv.org
Out-of-distribution (OOD) detection aims to detect test samples outside the training category
space, which is an essential component in building reliable machine learning systems …
space, which is an essential component in building reliable machine learning systems …
Mitigating the Modality Gap: Few-Shot Out-of-Distribution Detection with Multi-modal Prototypes and Image Bias Estimation
Y Wang, E Riddell, A Chow, S Sedwards… - arxiv preprint arxiv …, 2025 - arxiv.org
Existing vision-language model (VLM)-based methods for out-of-distribution (OOD)
detection typically rely on similarity scores between input images and in-distribution (ID) text …
detection typically rely on similarity scores between input images and in-distribution (ID) text …