| 2023 | CIKM | Post-hoc Selection of Pareto-Optimal Solutions in Search and Recommendation. | Vincenzo Paparella, Vito Walter Anelli, Franco Maria Nardini, Raffaele Perego, Tommaso Di Noia |
| 2023 | ECIR | Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering. | Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo |
| 2023 | RecSys | Reproducibility of Multi-Objective Reinforcement Learning Recommendation: Interplay between Effectiveness and Beyond-Accuracy Perspectives. | Vincenzo Paparella, Vito Walter Anelli, Ludovico Boratto, Tommaso Di Noia |
| 2023 | RecSys | Broadening the Scope: Evaluating the Potential of Recommender Systems beyond prioritizing Accuracy. | Vincenzo Paparella, Dario Di Palma, Vito Walter Anelli, Tommaso Di Noia |
| 2023 | SMC | A Pareto-Optimality-Based Approach for Selecting the Best Machine Learning Models in Mild Cognitive Impairment Prediction. | Paolo Sorino, Vincenzo Paparella, Domenico Lof, Tommaso Colafiglio, Eugenio Di Sciascio, Fedelucio Narducci, Rodolfo Sardone, Tommaso Di Noia |
| 2022 | RecSys | Pursuing Optimal Trade-Off Solutions in Multi-Objective Recommender Systems. | Vincenzo Paparella |
| 2021 | RecSys | Adherence and Constancy in LIME-RS Explanations for Recommendation (Long paper). | Vito Walter Anelli, Alejandro Bellogn, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo |