Experimental results on long-tailed CIFAR The comparison between the proposed hybrid networks and existing methods on long-tailed CIFAR datasets is presented in Table 1. The compared methods cover various categories of ideas for imbalanced classification, including loss re-weighting [7], margin modification [3], **data** augmentation [19], decoupling [37] and some other newly proposed ideas [34,13]. As can be seen from the table, our hybrid networks outperform the compared methods on almost all the settings.