Based on these equations, adding dependencybased word vector T is corresponding to considering a composite input [x i , T ] to the GRNN cell that concatenates the advanced continuous word embeddings and advanced dependency-based word embeddings.
gRUs have fewer parameters (U and W are smaller) and thus may train a bit faster or need less data to generalize.