Matrix spillover quantification represents a crucial challenge in complex learning. AI-driven approaches offer a novel solution by leveraging powerful algorithms to assess the extent of spillover effects between distinct matrix elements. This process boosts our knowledge of how information flows within neural networks, leading to improved model per