Characterizing and Mitigating the Impact of Data Imbalance for Stakeholders in Recommender Systems. - Elizabeth Gómez (RecSys, 2020)

Disparate Impact in Item Recommendation: A Case of Geographic Imbalance. - Elizabeth Gómez; Ludovico Boratto; Maria Salamó (ECIR (1), 2021)

The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems. - Elizabeth Gómez; Carlos Shui Zhang; Ludovico Boratto; Maria Salamó; Mirko Marras (SIGIR, 2021)

Enabling cross-continent provider fairness in educational recommender systems. - Elizabeth Gómez; Carlos Shui Zhang; Ludovico Boratto; Maria Salamó; Guilherme Ramos (Future Gener. Comput. Syst., 2022)

Provider fairness across continents in collaborative recommender systems. - Elizabeth Gómez; Ludovico Boratto; Maria Salamó (Inf. Process. Manag., 2022)

MOReGIn: Multi-Objective Recommendation at the Global and Individual Levels. - Elizabeth Gómez; David Contreras; Ludovico Boratto; Maria Salamó (ECIR (1), 2024)

AMBAR: A dataset for Assessing Multiple Beyond-Accuracy Recommenders. - Elizabeth Gómez; David Contreras; Ludovico Boratto; Maria Salamó (RecSys, 2024)

Bringing Equity to Coarse and Fine-Grained Provider Groups in Recommender Systems. - Elizabeth Gómez; David Contreras; Maria Salamó; Ludovico Boratto (UMAP, 2024)

Enhancing recommender systems with provider fairness through preference distribution-awareness. - Elizabeth Gómez; David Contreras; Ludovico Boratto; Maria Salamó (Int. J. Inf. Manag. Data Insights, 2025)