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CAP: Detecting Unauthorized Data Usage in Generative Models via Prompt Generation
Daniela Gallo, Angelica Liguori, Ettore Ritacco +3
To achieve accurate and unbiased predictions, Machine Learning (ML) models rely on large, heterogeneous, and high-quality datasets. However, this could raise ethical and legal conc…
Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferences
Erica Coppolillo, Simone Mungari, Ettore Ritacco +4
Digital platforms such as social media and e-commerce websites adopt Recommender Systems to provide value to the user. However, the social consequences deriving from their adoption…
Flexible Generation of Preference Data for Recommendation Analysis
Simone Mungari, Erica Coppolillo, Ettore Ritacco +1
Simulating a recommendation system in a controlled environment, to identify specific behaviors and user preferences, requires highly flexible synthetic data generation models capab…