16 citations · 18 across the 10 of their papers we have counts for
11 papers
When Numbers Start Talking: Numerical Signalling and Strategic Behaviour Among LLMs
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3
Large language model (LLM)-based agents increasingly operate in multi-agent systems (MAS) characterised by strategic interaction. However, little is known about whether, and to wha…
When Numbers Start Talking: Implicit Numerical Coordination Among LLM-Based Agents
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3
LLMs-based agents increasingly operate in multi-agent environments where strategic interaction and coordination are required. While existing work has largely focused on individual…
Can Media Act as a Soft Regulator of Safe AI Development? A Game Theoretical Analysis
Henrique Correia da Fonseca, António Fernandes, Zhao Song +15
When developers of artificial intelligence (AI) products need to decide between profit and safety for the users, they likely choose profit. Untrustworthy AI technology must come pa…
Can LLMs effectively provide game-theoretic-based scenarios for cybersecurity?
Daniele Proverbio, Alessio Buscemi, Alessandro Di Stefano +3
Game theory has long served as a foundational tool in cybersecurity to test, predict, and design strategic interactions between attackers and defenders. The recent advent of Large…
Strategic Communication and Language Bias in Multi-Agent LLM Coordination
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3
Large Language Model (LLM)-based agents are increasingly deployed in multi-agent scenarios where coordination is crucial but not always assured. Research shows that the way strateg…
Do LLMs trust AI regulation? Emerging behaviour of game-theoretic LLM agents
Alessio Buscemi, Daniele Proverbio, Paolo Bova +15
There is general agreement that fostering trust and cooperation within the AI development ecosystem is essential to promote the adoption of trustworthy AI systems. By embedding Lar…
FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theory
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3
Letting AI agents interact in multi-agent applications adds a layer of complexity to the interpretability and prediction of AI outcomes, with profound implications for their trustw…
Media and responsible AI governance: a game-theoretic and LLM analysis
Nataliya Balabanova, Adeela Bashir, Paolo Bova +15
This paper investigates the complex interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems. Using evolutionary game theory and large…
RogueGPT: dis-ethical tuning transforms ChatGPT4 into a Rogue AI in 158 Words
Alessio Buscemi, Daniele Proverbio
The ethical implications and potentials for misuse of Generative Artificial Intelligence are increasingly worrying topics. This paper explores how easily the default ethical guardr…
Large Language Models' Detection of Political Orientation in Newspapers
Alessio Buscemi, Daniele Proverbio
Democratic opinion-forming may be manipulated if newspapers' alignment to political or economical orientation is ambiguous. Various methods have been developed to better understand…
ChatGPT vs Gemini vs LLaMA on Multilingual Sentiment Analysis
Alessio Buscemi, Daniele Proverbio
Automated sentiment analysis using Large Language Model (LLM)-based models like ChatGPT, Gemini or LLaMA2 is becoming widespread, both in academic research and in industrial applic…