Specifically, MGL models each CLT process as heterogeneous information propagation over a dynamic graph, which captures latent language correlations and makes the downstream CLT adaptation more interpretable.
solely learning the dynamic graph structures may be insufficient since the graph-based metric space usually favors highresource languages over low-resource ones.