Weakness: There are some concerns authors should further address: 1)The transductive inference stage is essentially an ensemble of a serial of models. Especially, the proposed data perturbation can be considered as a common data augmentation. What if such an ensemble is applied to the existing transductive methods? And whether the flipping already is adopted in the data augmentation before the inputs fed to the network? 2)During meta-training, only the selected single path is used in one transductive step, what about the performance of optimizing all paths simultaneously? Given during inference all paths are utilized. 3)What about the performance of MCT (pair + instance)? 4)Why the results of Table 6 is not aligned with Table 1 (MCT-pair)? Also what about the ablation studies of MCT without the adaptive metrics. 5)Though this is not necessary, I'm curious about the performance of the SOTA method (e.g. LST) combined with the adaptive metric.
5)Though this is not necessary, I'm curious about the performance of the SOTA method (e.g. LST) combined with the adaptive metric.