We initialize the encoder and decoder weights using unsupervised pretraining and finetune these weights further during the supervised QG model training.
in each step of training, we update the weights W Esec , W E shared , W D shared and W Dsec using QG data in the secondary language and W E pri , W E shared , W D shared and W D pri using QG data in the primary language.