Our model is closely related to language models, as can be seen in section 2.2 and tables 1 and 2.
it has a lot in common with LSTMbased language models, as both train LSTM neural networks with the objective to predict target words based on their (short and long range) context, and both use techniques, such as negative sampling, to address large vocabulary computational challenges during training (Jozefowicz et al., 2016).