Unlocking the Black Box: Interpretable AI in NLP and Transformer Model Decisions
In the vast landscape of Natural Language Processing (NLP), the advent of transformer models has propelled the field forward, enabling remarkable advancements in language understanding and generation. However, as these models grow increasingly complex, there arises a critical need for interpretability— the ability to understand and explain the decisions made by these models. Interpretable AI in NLP revolves around the […]