Matrix spillover quantification represents a crucial challenge in complex learning. AI-driven approaches offer a promising solution by leveraging cutting-edge algorithms to assess the magnitude of spillover effects between different matrix elements. This process enhances our insights of how information transmits within neural networks, leading to i