EnCORE Workshop

The goal of this EnCORE workshop is to bring together researchers working on different aspects of interpretability in modern AI systems to enable Trustworthy AI. We aim to discuss recent advancements, theoretical foundations, and emerging directions across topics such as automated interpretability methods, representation and concept-level analysis, next-generation interpretable model architectures, trustworthiness and limitations of explanations, and new tools for understanding both deep vision models and large language models.

More broadly, the workshop seeks to consider how interpretability supports reliability, safety, and effective human oversight in AI. It will also highlight the growing significance of interpretability for the theoretical computer science and data science communities, where questions related to model structure, guarantees, abstraction, and reasoning have become increasingly central. By bringing these perspectives together, the workshop aims to foster deeper dialogue and shape future research directions in the study of transparent and understandable AI systems.