Matrix spillover quantification evaluates a crucial challenge in deep learning. AI-driven approaches offer a innovative solution by leveraging powerful algorithms to assess the extent of spillover effects between distinct matrix elements. This process enhances our understanding of how information flows within neural networks, leading to more model