Matrix spillover quantification represents a crucial challenge in deep learning. AI-driven approaches offer a novel solution by leveraging cutting-edge algorithms to interpret the level of spillover effects between different matrix elements. This process boosts our understanding of how information transmits within neural networks, leading to better