Paper recorded by Signals 4 on 2026-09-04 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07
Category: cs.CV · 计算机视觉 · first seen 2026-09-07
More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and circuit-based methods. Yet almost all of the field's effort has gone into building and comparing these methods, and little into the question they were meant to answer---how interpretable are our models, and are we making progress as they evolve? We