3 papers
cs.CL2026
PONTE: Personalized Orchestration for Natural Language Trustworthy Explanations
Vittoria Vineis, Matteo Silvestri, Lorenzo Antonelli +2
Explainable Artificial Intelligence (XAI) seeks to enhance the transparency and accountability of machine learning systems, yet most methods follow a one-size-fits-all paradigm tha…
cs.LG2025
Beyond Predictions: A Participatory Framework for Multi-Stakeholder Decision-Making
Vittoria Vineis, Giuseppe Perelli, Gabriele Tolomei
Conventional automated decision-support systems often prioritize predictive accuracy, overlooking the complexities of real-world settings where stakeholders' preferences may diverg…
cs.AI2025
One Search Fits All: Pareto-Optimal Eco-Friendly Model Selection
Filippo Betello, Antonio Purificato, Vittoria Vineis +2
The environmental impact of Artificial Intelligence (AI) is emerging as a significant global concern, particularly regarding model training. In this paper, we introduce GREEN (Guid…