RNN sequence-to-sequence models Bahdanau et al., 2015) are the state of the art for paradigm completion Kann and Schütze, 2016a;Cotterell et al., 2016a).
these models require a large amount of data to achieve competitive performance; this makes them unsuitable for out-of-thebox application to paradigm completion in the low-resource scenario.