@proceedings {973,
	title = {Error-margin Analysis for Hidden Neuron Activation Labels},
	journal = {18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024},
	year = {2024},
	publisher = {Springer },
	abstract = {<p>Understanding how high-level concepts are represented with- in artificial neural networks is a fundamental challenge in the field of arti- ficial intelligence. While existing literature in explainable AI emphasizes the importance of labeling neurons with concepts to understand their functioning, they mostly focus on identifying what stimulus activates a neuron in most cases; this corresponds to the notion of recall in informa- tion retrieval. We argue that this is only the first-part of a two-part job; it is imperative to also investigate neuron responses to other stimuli, i.e., their precision. We call this the neuron label{\textquoteright}s error margin.</p>
},
	keywords = {CNN, Concept Induction, Explainable AI},
	author = {Abhilekha Dalal and Rushrukh Rayan and Pascal Hitzler}
}
