Deep learning architectures are revolutionizing numerous fields, such as image recognition to natural language processing. However, their sophisticated nature often presents a challenge: understanding how these systems arrive at their outputs. This lack of explainability, often referred to as the "black box" problem, hinders our ability to fully tr