Matrix spillover quantification represents a crucial challenge in complex learning. AI-driven approaches offer a promising solution by leveraging cutting-edge algorithms to interpret the extent of spillover effects between separate matrix elements. This process improves our knowledge of how information flows within mathematical networks, leading to