We subsequently describe the architectures that we investigated for the sentence encoder, which, in our opinion, covers a suitable range of sentence encoders currently in use.
we examine standard recurrent models such as LSTMs and GRUs, for which we investigate mean and maxpooling over the hidden representations; a selfattentive network that incorporates different views of the sentence; and a hierarchical convolutional network that can be seen as a tree-based method that blends different levels of abstraction.