Learning by Self-Explaining (LSX): A Novel Approach to Enhancing AI Generalization and Faithful Model Explanations through Self-Refinement

" data-medium-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-11-at-1.09.00-AM-300x182.png" data-large-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-11-at-1.09.00-AM-1024x622.png" tabindex="0" role="button"> " data-medium-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-11-at-1.09.00-AM-300x182.png" data-large-file="https://www.marktechpost.com/wp-content/uploads/2024/09/Screenshot-2024-09-11-at-1.09.00-AM-1024x622.png" tabindex="0" role="button">Explainable AI (XAI) has emerged as a critical field, focusing on providing interpretable insights into machine learning model decisions. Self-explaining models, utilizing techniques such as backpropagation-based, model distillation, and prototype-based approaches, aim to elucidate decision-making processes. However, most existing studies treat explanations as one-way communication tools for model inspection, neglecting their potential to actively contribute […]

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