Who Needs Labels? Adapting Vision Foundation Models With the Metadata You Already Have 事件

Who Needs Labels? Adapting Vision Foundation Models With the Metadata You Already Have arXiv:2606.05107v1 Announce Type: new Abstract: We propose a label-free approach to adapt powerful but generic vision foundation models to specialized scientific domains. Standard supervised fine-tuning is often ill-suited to these settings: labels are scarce, and task-specific training can collapse the model's generality and hurt robustness. We instead leverage metadata to adapt representations to new domain