Interpretability and Model Editing in Large Language Models

Learn about the principles of model interpretability and editing techniques in this comprehensive lecture by Northeastern University Assistant Professor David Bau at UC Berkeley EECS. Dive deep into understanding how to analyze, interpret, and modify machine learning models, with a focus on making AI systems more transparent and controllable. Explore advanced concepts in model interpretability that help bridge the gap between theoretical understanding and practical applications in AI development.