8 papers
D-Score: A Spectral Hidden-State Signal for Hallucination Detection in Large Language Models
Bianca Raimondi, Davide Evangelista, Maurizio Gabbrielli +1
Large Language Models can produce fluent text that is false, unsupported by the available evidence, or inconsistent with information that appears to be internally represented by th…
Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration
Davide Evangelista, Elena Morotti, Francesco Pivi +1
Diffusion-based posterior sampling (PS) is a leading framework for imaging inverse problems, combining learned priors with measurement constraints. Yet, its standard formulations r…
CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments
Isabella Marasco, Davide Evangelista, Elena Loli Piccolomini +1
Artificial intelligence systems predominantly rely on static data distributions, making them ineffective in dynamic real-world environments, such as cybersecurity, autonomous trans…
A Diffusion-Based Generative Prior Approach to Sparse-view Computed Tomography
Davide Evangelista, Pasquale Cascarano, Elena Loli Piccolomini
The reconstruction of X-rays CT images from sparse or limited-angle geometries is a highly challenging task. The lack of data typically results in artifacts in the reconstructed im…
Series-Parallel and Planar Graphs for Efficient Broadcasting
David Evangelista, Hovhannes A. Harutyunyan, Aram Khanlari
The broadcasting problem concerns the efficient dissemination of information in graphs. In classical broadcasting, a single originator vertex initially has a message to be transmit…
Adaptive Weighted Total Variation boosted by learning techniques in few-view tomographic imaging
Elena Morotti, Davide Evangelista, Andrea Sebastiani +1
This study presents the development of a spatially adaptive weighting strategy for Total Variation regularization, aimed at addressing under-determined linear inverse problems. The…