Researchers are exploring various methods for community detection in complex networks, including the use of graph convolution networks and graph attention networks. Different approaches, such as adaptive feature and topology learning, reduced network extremal ensemble learning, and local dominance, are being proposed to identify communities and vital nodes. The effectiveness of these methods in detecting community boundaries and structures in networks is being investigated.