5 papers · 1 filter
Exploring Approaches for Detecting Memorization of Recommender System Data in Large Language Models
Antonio Colacicco, Vito Guida, Dario Di Palma +2
Large Language Models (LLMs) are increasingly applied in recommendation scenarios due to their strong natural language understanding and generation capabilities. However, they are…
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…
Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation
Claudio Pomo, Matteo Attimonelli, Danilo Danese +2
Multimodal Recommender Systems aim to improve recommendation accuracy by integrating heterogeneous content, such as images and textual metadata. While effective, it remains unclear…
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…
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…