Researchers are exploring methods for embedding directed networks into euclidean and hyperbolic spaces. Various approaches are being investigated, including symmetry-driven embedding, greedy routing optimization, and iterative embedding and reweighting. These methods aim to effectively map complex networks into multidimensional spaces, with some focusing on community structure and others on growing networks beyond two dimensions.