Matrix spillover quantification measures a crucial challenge in complex learning. AI-driven approaches offer a novel solution by leveraging powerful algorithms to interpret the level of spillover effects between distinct matrix elements. This process improves our knowledge of how information flows within mathematical networks, leading to more model