Instead of training the LSTM T&N and LC models separately and then concatenating their output representations, we propose a framework where both models are trained jointly, and where the final network has then the capacity to predict AES scores and flag adversarial input (Figure 3).
the LSTM T&N and LC networks predict an essay and coherence score respectively (as described earlier), but now they both share the word embedding layer.