3 papers
cs.LG2026
A Unifying Framework of Concept-based Explainable AI with Completeness Guarantees
Vojtěch Kůr, Adam Kukučka, Tomáš Brázdil +1
Concept-based explanations describe neural network predictions through human-understandable properties of inputs called concepts. The field encompasses approaches that differ in ho…
cs.CV2026
Weakly Supervised Multicenter Nancy Index Scoring in Ulcerative Colitis Using Foundation Models
Adam Kukučka, Ondřej Fabián, Vít Musil +1
Histologic assessment of ulcerative colitis (UC) activity is an important endpoint in clinical trials and routine care, but manual grading with indices such as the Nancy histologic…
cs.CV2025
LLEXICORP: End-user Explainability of Convolutional Neural Networks
Vojtěch Kůr, Adam Bajger, Adam Kukučka +3
Convolutional neural networks (CNNs) underpin many modern computer vision systems. With applications ranging from common to critical areas, a need to explain and understand the mod…