1 citations · 2 across the 11 of their papers we have counts for
4 papers · 1 filter
Retrieval-Augmented Visual Prompting: Guiding Foundation Models in Two-Photon Imaging
Salvatore Calcagno, Marco Finocchiaro, Giovanni Bellitto +3
Two-photon calcium imaging presents a challenging setting for foundation models: image appearance varies substantially across recordings and experimental conditions, annotations ar…
DEXTER: Diffusion-Guided EXplanations with TExtual Reasoning for Vision Models
Simone Carnemolla, Matteo Pennisi, Sarinda Samarasinghe +5
Understanding and explaining the behavior of machine learning models is essential for building transparent and trustworthy AI systems. We introduce DEXTER, a data-free framework th…
Diffexplainer: Towards Cross-modal Global Explanations with Diffusion Models
Matteo Pennisi, Giovanni Bellitto, Simone Palazzo +2
We present DiffExplainer, a novel framework that, leveraging language-vision models, enables multimodal global explainability. DiffExplainer employs diffusion models conditioned on…
Selective Attention-based Modulation for Continual Learning
Giovanni Bellitto, Federica Proietto Salanitri, Matteo Pennisi +5
We present SAM, a biologically-plausible selective attention-driven modulation approach to enhance classification models in a continual learning setting. Inspired by neurophysiolog…