2 citations · 3 across the 13 of their papers we have counts for
7 papers · 1 filter
Certification of Real Images through Calibrated Content Authentication
Sarim Hashmi, Abdelrahman Elsayed, Mohammed Talha Alam +2
Generative models can synthesize high-quality inauthentic multimedia content that is already being misused at scale. We evaluate twenty deepfake detectors against ten generators re…
ShieldCLIP: Selective Safety Alignment for Harmful Content Mitigation in Multimodal Foundation Models
Tobia Poppi, Silvia Cappelletti, Samuele Poppi +4
Multimodal encoders such as CLIP underlie many downstream systems, but their web-scale training data embed harmful associations that safety alignment must suppress without unnecess…
ReACT-CLIP: Response-Aware Test-Time Defense for Vision--Language Models
Hashmat Shadab Malik, Toluwani Aremu, Samuele Poppi +2
Training-free test-time defenses offer a practical way to improve the adversarial robustness of CLIP-style vision--language models without modifying the pretrained model. However,…
Robust and Calibrated Detection of Authentic Multimedia Content
Sarim Hashmi, Abdelrahman Elsayed, Mohammed Talha Alam +2
Generative models can synthesize highly realistic content, so-called deepfakes, that are already being misused at scale to undermine digital media authenticity. Current deepfake de…
Safe-CLIP: Removing NSFW Concepts from Vision-and-Language Models
Samuele Poppi, Tobia Poppi, Federico Cocchi +3
Large-scale vision-and-language models, such as CLIP, are typically trained on web-scale data, which can introduce inappropriate content and lead to the development of unsafe and b…
Multi-Class Unlearning for Image Classification via Weight Filtering
Samuele Poppi, Sara Sarto, Marcella Cornia +2
Machine Unlearning is an emerging paradigm for selectively removing the impact of training datapoints from a network. Unlike existing methods that target a limited subset or a sing…
Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis
Samuele Poppi, Marcella Cornia, Lorenzo Baraldi +1
As the request for deep learning solutions increases, the need for explainability is even more fundamental. In this setting, particular attention has been given to visualization te…