102 citations · 384 across the 37 of their papers we have counts for
6 papers · 1 filter
Evaluating ChatGPT as a Recommender System: A Rigorous Approach
Dario Di Palma, Giovanni Maria Biancofiore, Vito Walter Anelli +3
Large Language Models (LLMs) have recently shown impressive abilities in handling various natural language-related tasks. Among different LLMs, current studies have assessed ChatGP…
A Topology-aware Analysis of Graph Collaborative Filtering
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli +3
The successful integration of graph neural networks into recommender systems (RSs) has led to a novel paradigm in collaborative filtering (CF), graph collaborative filtering (graph…
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis
Vito Walter Anelli, Daniele Malitesta, Claudio Pomo +3
The success of graph neural network-based models (GNNs) has significantly advanced recommender systems by effectively modeling users and items as a bipartite, undirected graph. How…
Post-hoc Selection of Pareto-Optimal Solutions in Search and Recommendation
Vincenzo Paparella, Vito Walter Anelli, Franco Maria Nardini +2
Information Retrieval (IR) and Recommender Systems (RS) tasks are moving from computing a ranking of final results based on a single metric to multi-objective problems. Solving the…
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning
Giandomenico Cornacchia, Vito Walter Anelli, Fedelucio Narducci +2
The increasing application of Artificial Intelligence and Machine Learning models poses potential risks of unfair behavior and, in light of recent regulations, has attracted the at…
Counterfactual Reasoning for Bias Evaluation and Detection in a Fairness under Unawareness setting
Giandomenico Cornacchia, Vito Walter Anelli, Fedelucio Narducci +2
Current AI regulations require discarding sensitive features (e.g., gender, race, religion) in the algorithm's decision-making process to prevent unfair outcomes. However, even wit…