collaborators

5 papers

cs.CL2025

Inverse Language Modeling towards Robust and Grounded LLMs

Davide Gabrielli, Simone Sestito, Iacopo Masi

The current landscape of defensive mechanisms for LLMs is fragmented and underdeveloped, unlike prior work on classifiers. To further promote adversarial robustness in LLMs, we pro…

cs.LG2025

Understanding Adversarial Training with Energy-based Models

Mujtaba Hussain Mirza, Maria Rosaria Briglia, Filippo Bartolucci +3

We aim at using Energy-based Model (EBM) framework to better understand adversarial training (AT) in classifiers, and additionally to analyze the intrinsic generative capabilities…

cs.CV2025

What is Adversarial Training for Diffusion Models?

Briglia Maria Rosaria, Mujtaba Hussain Mirza, Giuseppe Lisanti +1

We answer the question in the title, showing that adversarial training (AT) for diffusion models (DMs) fundamentally differs from classifiers: while AT in classifiers enforces outp…

cs.CV2024

Language-guided Hierarchical Fine-grained Image Forgery Detection and Localization

Xiao Guo, Xiaohong Liu, Iacopo Masi +1

Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make a unified image forgery detection and locali…

cs.CV2024

Environment Maps Editing using Inverse Rendering and Adversarial Implicit Functions

Antonio D'Orazio, Davide Sforza, Fabio Pellacini +1

Editing High Dynamic Range (HDR) environment maps using an inverse differentiable rendering architecture is a complex inverse problem due to the sparsity of relevant pixels and the…