Detailed Instructions: In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.
Q: Community detection in graphs is of central importance in graph mining, machine learning and network science. Detecting overlapping communities is especially challenging, and remains an open problem . Motivated by the success of graph-based deep learning in other graph-related tasks, we study the applicability of this framework for overlapping community detection . We propose a probabilistic model for overlapping community detection based on the graph neural network architecture . Despite its simplicity, our model outperforms the existing approaches in the community recovery task by a large margin . Moreover, due to the inductive formulation, the proposed model is able to perform out-of-sample community detection for nodes that were not present at training time
A:
Detecting overlapping communities in graphs using graph neural networks