The multi-task learning model for IDRR aims to predict the discourse relations and the implicit connectives simultaneously in a single training process so the knowledge from the connective prediction can be transferred to the relation prediction to improve the performance.
the arguments A 1 and A 2 are first consumed by a neural network model M (called the encoder model) to generate a representation vector V = M (A 1 , A 2 ).