Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization

arXiv:2507.02288v2 Announce Type: replace-cross Abstract: Domain Generalization (DG) seeks to develop a versatile model capable of performing effectively on unseen target domains. Notably, recent advances in pre-trained Visual Foundation Models (VFMs), such as CLIP, have demonstrated considerable potential in enhancing the generalization capabilities of deep learning models. Despite the increasing attention toward VFM-based domain prompt tuning within DG, the effective design of prompts capable of disentangling invariant features across diverse domains remains a critical challenge. In this pap

Source: arXiv cs.LG — read the full report at the original publisher.

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