If the salient data record is the same as the previous one (Z t = 0), it predicts the next word y t via a probability over words conditioned on the context vector h t : Subsequently, the hidden state of language model h LM is updated: where y t is the embedding of the word generated at time step t. 4 We also incorporate the information about the writer of the summaries into our model.
instead of using Equation 9, we concatenate the embedding w of a writer to to construct context vector h t : where W H is a new weight matrix.