9 citations · 17 across the 13 of their papers we have counts for
4 papers · 1 filter
eval-unlearn: Benchmarking unlearning in Text-to-Image Diffusion Models
Mansi, Nikhil Raghavan, Zixia Huang +4
The rising number of concept unlearning techniques for text-to-image (T2I) diffusion models has produced a fragmented evaluation landscape. Methods are assessed under heterogeneous…
Certifying Concept Unlearning in Text-to-Image Diffusion Models
Mansi, Luca Marzari, Francesco Leofante
Existing evaluations of concept unlearning in text-to-image (T2I) diffusion models primarily rely on attack success rates obtained through automated adversarial prompt search. Howe…
Efficient bias mitigation in T2I diffusion models using Concept Graphs
Mansi, Avinash Kori, Francesco Leofante
Text-to-Image diffusion models often propagate harmful bias inherited from the training data. Existing bias mitigation techniques typically intervene only at the text encoder or pr…
Attribution-based Explanations for Markov Decision Processes
Paul Kobialka, Andrea Pferscher, Francesco Leofante +3
Attribution techniques explain the outcome of an AI model by assigning a numerical score to its inputs. So far, these techniques have mainly focused on attributing importance to st…