Also in development are graph-neural networks that could leverage QTAIM-descriptors while avoiding computationallyexpensive message-passing graph neural networks. The aim here would be to rely on QTAIM descriptors to capture distal relationships between nodes (atom, bonds) rather than using iterative message-passing steps to achieve this task. From a conceptual DFT standpoint, the native integration of parsers and data structures that support ring and cage critical points would be beneficial.