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cs.LG2026
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…
cs.LG2026
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…
cs.LG2025
Understanding Dementia Speech Alignment with Diffusion-Based Image Generation
Mansi, Anastasios Lepipas, Dominika Woszczyk +2
Text-to-image models generate highly realistic images based on natural language descriptions and millions of users use them to create and share images online. While it is expected…