Selective Prediction Forgetting for Adaptation of Weakly Supervised Localization of Histology Images

Under strong cross-domain shifts, weakly supervised object localization (WSOL) models often lose their capacity to discriminate and develop a strong prediction bias toward a subset of classes. As a result, the majority of target samples are assigned to these dominant classes. Since source-free (unsu