Abstract: Domain generalization (DG) aims to train a model on source domains that can generalize well to unseen domains. Recent advances in Vision-Language Models (VLMs), such as CLIP, exhibit ...

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Abstract: Traditional Unsupervised Domain Adaptation (UDA) leverages the labeled source domain to tackle the learning tasks on the unlabeled target domain. It can be more challenging when a large ...