Hidden Neuron Activation

Understanding how individual neurons within deep learning models, particularly convolutional neural networks (CNNs), activate in response to input data is a crucial challenge in Explainable AI (XAI). Current research focuses on developing automated methods to interpret these activations, often leveraging large-scale knowledge bases and symbolic reasoning techniques to assign meaningful labels to neurons and assess the accuracy of these labels. This work aims to demystify the "black box" nature of deep learning by providing insights into how these systems process information, ultimately improving model transparency and trustworthiness for both scientific understanding and practical applications.