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cs.CV2025
Revisiting Logit Distributions for Reliable Out-of-Distribution Detection
Jiachen Liang, Ruibing Hou, Minyang Hu +3
Out-of-distribution (OOD) detection is critical for ensuring the reliability of deep learning models in open-world applications. While post-hoc methods are favored for their effici…
cs.CV2024
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models
Jiachen Liang, Ruibing Hou, Minyang Hu +3
Pre-trained vision-language models (e.g., CLIP) have shown powerful zero-shot transfer capabilities. But they still struggle with domain shifts and typically require labeled data t…
cs.CV2024
Task Attribute Distance for Few-Shot Learning: Theoretical Analysis and Applications
Minyang Hu, Hong Chang, Zong Guo +3
Few-shot learning (FSL) aims to learn novel tasks with very few labeled samples by leveraging experience from \emph{related} training tasks. In this paper, we try to understand FSL…