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Found 2 papers, 1 papers with code
Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models
Large-scale vision-language models (VLMs) have shown a strong zero-shot generalization capability on unseen-domain data.
Semi-Supervised Domain Adaptation with Source Label Adaptation
Semi-Supervised Domain Adaptation (SSDA) involves learning to classify unseen target data with a few labeled and lots of unlabeled target data, along with many labeled source data from a related domain.
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