They describe a neural model for text generation, which keeps track of a checklist of items that need to be mentioned in the text.
The basic system is an encoder-decoder GRU model for text generation. On top of that, the model uses attention over items that need to be mentioned and items that have already been mentioned, both of which are encoded as vectors. An additional cost objective encourages the checklist to be filled by the end of the text. Evaluation is performed on recipe and dialogue generation.