28 citations · 28 across the 15 of their papers we have counts for
17 papers
TORINO: Token Reduction via Interpretable Concept Overlap in Vision-Language Models
Riccardo Renzulli, Gabriele Spadaro, Shruthi Gowda +2
Vision-Language Models (VLMs) have demonstrated impressive capabilities across different tasks, but their computational cost is dominated by the large number of visual tokens fed t…
Look But Don't Touch with Sparse Autoencoders for Unlearning in Diffusion Models
Enrico Cassano, Riccardo Renzulli, Rayyan Ahmed +2
Sparse autoencoders (SAEs) have recently been proposed as interpretable tools for concept-level manipulation, under the assumption that isolated features can serve as controllable…
Cardiac Output Prediction from Echocardiograms: Self-Supervised Learning with Limited Data
Adson Duarte, Davide Vitturini, Emanuele Milillo +9
Cardiac Output (CO) is a key parameter in the diagnosis and management of cardiovascular diseases. However, its accurate measurement requires right-heart catheterization, an invasi…
Synthetic Dataset Generation and Validation for Robotic Surgery Instrument Segmentation
Giorgio Chiesa, Rossella Borra, Vittorio Lauro +5
This paper presents a comprehensive workflow for generating and validating a synthetic dataset designed for robotic surgery instrument segmentation. A 3D reconstruction of the Da V…
Automated Prediction of Paravalvular Regurgitation before Transcatheter Aortic Valve Implantation
Michele Cannito, Riccardo Renzulli, Adson Duarte +9
Severe aortic stenosis is a common and life-threatening condition in elderly patients, often treated with Transcatheter Aortic Valve Implantation (TAVI). Despite procedural advance…
MedSAE: Dissecting MedCLIP Representations with Sparse Autoencoders
Riccardo Renzulli, Colas Lepoutre, Enrico Cassano +1
Artificial intelligence in healthcare requires models that are accurate and interpretable. We advance mechanistic interpretability in medical vision by applying Medical Sparse Auto…