3 papers
cs.CV2026
MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification
Nikola JoviÅ¡iÄ, Milica Å kipina, Nicola Dall'Asen +1
Modern foundation models provide highly expressive visual representations, yet adapting them to high-resolution medical imaging remains challenging due to limited annotations and w…
eess.IV2025
MAMBO: High-Resolution Generative Approach for Mammography Images
Milica Å kipina, Nikola JoviÅ¡iÄ, Nicola Dall'Asen +5
Mammography is the gold standard for the detection and diagnosis of breast cancer. This procedure can be significantly enhanced with Artificial Intelligence (AI)-based software, wh…
cs.CY2025
CERN for AI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment
Ljubisa Bojic, Matteo Cinelli, Dubravko Culibrk +1
This paper explores the potential of a multidisciplinary approach to testing and aligning artificial intelligence (AI), specifically focusing on large language models (LLMs). Due t…