Hao-Yu Jiang

Protodetect: Prototype Compactness and Inference Calibration for Few-Shot Out-of-Distribution Detection

Detecting out-of-distribution (OOD) samples from limited labeled data is important for reliable recognition under semantic novelty. Existing few-shot approaches use synthetic or auxiliary unknowns, model only in-distribution (ID) data, or rely on large pretrained vision–language models. This paper presents Protodetect,...