Question: Which future direction in NLG are discussed?
Answer: 1) How to introduce unsupervised pre-training into NLG tasks with cross-modal context?, 2) How to design a generic pre-training algorithm to fit a wide range of NLG tasks?, 3) How to reduce the computing resources required for large-scale pre-training?, 4) What aspect of knowledge do the pre-trained models provide for better language generation?