51 citations · 171 across the 25 of their papers we have counts for
25 papers · 1 filter
Exploring Diversity, Novelty, and Popularity Bias in ChatGPT's Recommendations
Dario Di Palma, Giovanni Maria Biancofiore, Vito Walter Anelli +2
ChatGPT has emerged as a versatile tool, demonstrating capabilities across diverse domains. Given these successes, the Recommender Systems (RSs) community has begun investigating i…
On the Impact of Graph Neural Networks in Recommender Systems: A Topological Perspective
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli +3
In recommender systems, user-item interactions can be modeled as a bipartite graph, where user and item nodes are connected by undirected edges. This graph-based view has motivated…
Balancing Accuracy and Novelty with Sub-Item Popularity
Chiara Mallamaci, Aleksandr Vladimirovich Petrov, Alberto Carlo Maria Mancino +3
In the realm of music recommendation, sequential recommenders have shown promise in capturing the dynamic nature of music consumption. A key characteristic of this domain is repeti…
Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M
Dario Di Palma, Felice Antonio Merra, Maurizio Sfilio +3
Large Language Models (LLMs) have become increasingly central to recommendation scenarios due to their remarkable natural language understanding and generation capabilities. Althou…
Enhancing Sequential Music Recommendation with Personalized Popularity Awareness
Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia +2
In the realm of music recommendation, sequential recommender systems have shown promise in capturing the dynamic nature of music consumption. Nevertheless, traditional Transformer-…
A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli +3
Recently, graph neural networks (GNNs)-based recommender systems have encountered great success in recommendation. As the number of GNNs approaches rises, some works have started q…