x 3 x n Bidirectional RNNs have also proven to be quite effective for sequence classification. Recall from Fig. 9 .8 that for sequence classification we used the final hidden state of the RNN as the input to a subsequent feedforward classifier. A difficulty with this approach is that the final state naturally reflects more information about the end of the sentence than its beginning. Bidirectional RNNs provide a simple solution to this problem; as shown in Fig. 9 .12, we simply combine the final hidden states from the forward and backward passes (for example by concatenation) and use that as input for follow-on processing.