KAIST XAI Tutorial 2025 | Fast and Faithful Explanations | Youngjin Park (SAIL, KAIST)

This presentation introduces XAI acceleration method for real-time explanation of black-box ML/AI models in financial regulatory environments. While model-agnostic methods such as SHAP and LIME are widely used for complex black-box models in industry, they suffer from computational costs that scale with the number of baselines. Existing acceleration approaches lack theoretical grounding, relying on arbitrary statistical values (e.g., zero, mean) as baselines or depending on additional complex learable models. In this work, we formulate baseline selection as a Column Subset Selection Problem (C…