activity
20222024
most citedFair Augmentation for Graph Collaborative Filtering

9 citations · 20 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2024

LIMBA: An Open-Source Framework for the Preservation and Valorization of Low-Resource Languages using Generative Models

Salvatore Mario Carta, Stefano Chessa, Giulia Contu +19

Minority languages are vital to preserving cultural heritage, yet they face growing risks of extinction due to limited digital resources and the dominance of artificial intelligenc…

cs.CV2024

Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection

Sondos Mohamed, Walter Zimmer, Ross Greer +6

Accurately detecting 3D objects from monocular images in dynamic roadside scenarios remains a challenging problem due to varying camera perspectives and unpredictable scene conditi…

cs.IR20249 cited

Fair Augmentation for Graph Collaborative Filtering

Ludovico Boratto, Francesco Fabbri, Gianni Fenu +2

Recent developments in recommendation have harnessed the collaborative power of graph neural networks (GNNs) in learning users' preferences from user-item networks. Despite emergin…

cs.CV20241 cited

If It's Not Enough, Make It So: Reducing Authentic Data Demand in Face Recognition through Synthetic Faces

Andrea Atzori, Fadi Boutros, Naser Damer +2

Recent advances in deep face recognition have spurred a growing demand for large, diverse, and manually annotated face datasets. Acquiring authentic, high-quality data for face rec…

cs.IR2024

Robustness in Fairness against Edge-level Perturbations in GNN-based Recommendation

Ludovico Boratto, Francesco Fabbri, Gianni Fenu +2

Efforts in the recommendation community are shifting from the sole emphasis on utility to considering beyond-utility factors, such as fairness and robustness. Robustness of recomme…

cs.IR2024

A Cost-Sensitive Meta-Learning Strategy for Fair Provider Exposure in Recommendation

Ludovico Boratto, Giulia Cerniglia, Mirko Marras +2

When devising recommendation services, it is important to account for the interests of all content providers, encompassing not only newcomers but also minority demographic groups.…