1 citations · 1 across the 2 of their papers we have counts for
12 papers
Architectural Backdoors in Vision-Language Model Supply Chains via Representation Steering
Maria Rosaria Briglia, Igor Maljkovic, Antonio Emanuele Cinà +3
Vision--Language Models (VLMs) are increasingly deployed through a model supply chain in which pretrained checkpoints, architecture definitions, text encoders, and exported computa…
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
Srishti Gupta, Zhang Chen, Luca Demetrio +9
Thanks to their extensive capacity, over-parameterized neural networks exhibit superior predictive capabilities and generalization. However, having a large parameter space is consi…
Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization
Igor Maljkovic, Maria Rosaria Briglia, Iacopo Masi +2
Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual information in a shared embedding sp…
Rethinking Robustness in Machine Learning: A Posterior Agreement Approach
João Borges S. Carvalho, Victor Jimenez Rodriguez, Alessandro Torcinovich +4
The robustness of algorithms against covariate shifts is a fundamental problem with critical implications for the deployment of machine learning algorithms in the real world. Curre…
Evaluating the Evaluators: Trust in Adversarial Robustness Tests
Antonio Emanuele CinÃ, Maura Pintor, Luca Demetrio +3
Despite significant progress in designing powerful adversarial evasion attacks for robustness verification, the evaluation of these methods often remains inconsistent and unreliabl…
On the Robustness of Adversarial Training Against Uncertainty Attacks
Emanuele Ledda, Giovanni Scodeller, Daniele Angioni +5
In learning problems, the noise inherent to the task at hand hinders the possibility to infer without a certain degree of uncertainty. Quantifying this uncertainty, regardless of i…