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