We invite submission of papers describing innovative research and applications around the following topics. Papers that introduce new theoretical concepts or methods, help to develop a better understanding of new emerging concepts through extensive experiments, or demonstrate a novel application of these methods to a domain is encouraged. Topics include (but not limited to) the following:

* Automatic graph construction for NLP
* Graph representation learning for NLP
* Graph2seq, graph2tree, and graph2graph models for NLP
* Deep reinforcement learning on graphs for NLP
* Adversarial deep learning on graphs for NLP
* GNN based representation learning on knowledge graphs

Please check the website of the workshop for more information.