10 citations · 11 across the 9 of their papers we have counts for
5 papers · 1 filter
Engagement-Driven Content Generation with Large Language Models
Erica Coppolillo, Federico Cinus, Marco Minici +2
Large Language Models (LLMs) demonstrate significant persuasive capabilities in one-on-one interactions, but their influence within social networks, where interconnected users and…
Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferences
Erica Coppolillo, Simone Mungari, Ettore Ritacco +4
Digital platforms such as social media and e-commerce websites adopt Recommender Systems to provide value to the user. However, the social consequences deriving from their adoption…
Relevance meets Diversity: A User-Centric Framework for Knowledge Exploration through Recommendations
Erica Coppolillo, Giuseppe Manco, Aristides Gionis
Providing recommendations that are both relevant and diverse is a key consideration of modern recommender systems. Optimizing both of these measures presents a fundamental trade-of…
LLASP: Fine-tuning Large Language Models for Answer Set Programming
Erica Coppolillo, Francesco Calimeri, Giuseppe Manco +2
Recently, Large Language Models (LLMs) have showcased their potential in various natural language processing tasks, including code generation. However, while significant progress h…
Flexible Generation of Preference Data for Recommendation Analysis
Simone Mungari, Erica Coppolillo, Ettore Ritacco +1
Simulating a recommendation system in a controlled environment, to identify specific behaviors and user preferences, requires highly flexible synthetic data generation models capab…