The Jacobian matrix is a fundamental mathematical construct in multivariable calculus that plays a significant role in the analysis and optimization of neural networks, particularly in the context of understanding sensitivity and implicit attention mechanisms. In the realm of advanced deep learning, the Jacobian matrix is instrumental in examining how small changes in input features