While this idea is simple and intuitive, we found that it alone was not enough to achieve competitive accuracy with real NMT models.
we make two improvements: First, we propose a hybrid model, where the high frequency words are predicted by a standard softmax, and low frequency words are predicted by the proposed binary codes separately.