Explainable Artificial Intelligence (XAI)
This cluster of papers focuses on Explainable Artificial Intelligence (XAI) and the development of interpretable models, visual explanations, and responsible machine learning interpretability. It explores concepts, challenges, and opportunities in XAI, including the use of gradient-based localization, understanding deep neural networks, feature importance, and addressing black box models. The papers also discuss the responsibility and ethical considerations in AI.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.