For words not in the training data WMask is reduced, like FullLex, to the Matrix model.
to the FullLex model, which uses crosswise transformations of the input vectors, A v u and A u v, Dima (2015) uses direct transformations: u, the vector of the first word, is transformed via element-wise multiplication with its first position mask, u m , u u m .