136 citations · 412 across the 29 of their papers we have counts for
6 papers · 1 filter
FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data
Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez +44
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must…
Faithful Path Language Modeling for Explainable Recommendation over Knowledge Graph
Giacomo Balloccu, Ludovico Boratto, Christian Cancedda +2
The integration of path reasoning with language modeling in recommender systems has shown promise for enhancing explainability but often struggles with the authenticity of the expl…
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems
Ludovico Boratto, Francesco Fabbri, Gianni Fenu +2
In recommendation literature, explainability and fairness are becoming two prominent perspectives to consider. However, prior works have mostly addressed them separately, for insta…
(Un)fair Exposure in Deep Face Rankings at a Distance
Andrea Atzori, Gianni Fenu, Mirko Marras
Law enforcement regularly faces the challenge of ranking suspects from their facial images. Deep face models aid this process but frequently introduce biases that disproportionatel…
GNNUERS: Fairness Explanation in GNNs for Recommendation via Counterfactual Reasoning
Giacomo Medda, Francesco Fabbri, Mirko Marras +2
Nowadays, research into personalization has been focusing on explainability and fairness. Several approaches proposed in recent works are able to explain individual recommendations…
Knowledge is Power, Understanding is Impact: Utility and Beyond Goals, Explanation Quality, and Fairness in Path Reasoning Recommendation
Giacomo Balloccu, Ludovico Boratto, Christian Cancedda +2
Path reasoning is a notable recommendation approach that models high-order user-product relations, based on a Knowledge Graph (KG). This approach can extract reasoning paths betwee…