Text-Embedding Loss: Motivated by the popularity of deep architectures for visual question answering, that combine a global CNN image representation with an LSTM [7] question representation [4, 13, 17, 20, 29, 30, 31] , as well as the leading performance of nCCA on the multi-choice <cite>Visual Madlibs task</cite> <cite>[32]</cite> , we propose a novel extension of the CNN+LSTM architecture that chooses a prompt completion out of four candidates (see Figure 4 ) by measuring similarities directly in the embedding space.