Deep learning algorithms are revolutionizing numerous fields, including image recognition to natural language processing. However, their sophisticated nature often presents a challenge: understanding how these networks arrive at their outputs. This lack of interpretability, often referred to as the "black box" problem, hinders our ability to comple