Before revision:  Domain generalization (DG), i.e., out-of-distribution generalization, has attracted increased interests in recent years.
After revision: Machine learning systems generally assume that the training and testing distributions are the same. To this end, a key requirement is to develop models that can generalize to unseen distributions. Domain generalization (DG), i.e., out-of-distribution generalization, has attracted increased interests in recent years.