The hidden state at time-step t is updated via the GRU unit based on the previous hidden state and the input word.
: where h 0 ∈ R n is the decoder's initial hidden state and h t ∈ R n is the hidden state at time-step t. To fully exploit the encoder-side information, we apply an attention fusion layer to summarize the output of each encoder and jointly determine the final word distribution.