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