Thus, instead of having the seq2seq model learn patterns of language only from aligned parallel corpora, we assist the model by providing it closely related (similar) samples from the training data that it can refer to while generating text.
given a context c, we retrieve a set  Table 1: Sample input contexts and corresponding gold responses from Ubuntu validation dataset along with similar contexts seen in training data and their corresponding responses.