This is in line with our hypothesis that explicit modeling of morphology may capture interactions of elements in the sequence and allow for better generalization thereof.
with MLPs and CNNs, RNNs consider the entire sequence for classification, and so it may be the case that previously unseen tokens in the sequence may undermine classification in token-based settings.