Browse 3 peer-reviewed papers from Fondazione Bruno Kessle spanning Conversational Persuasion of LLM, Human-Computer Interaction (2024–2025). Research powered by Prolific's high-quality participant data.
This page lists 3 peer-reviewed papers from researchers at Fondazione Bruno Kessle in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: F Salvi, M Horta Ribeiro, R Gallotti, R West
Year: 2025
Published in: Nature Human Behaviour, 2025 - nature.com
Institution: EPFL, Fondazione Bruno Kessle, Princeton University
Research Area: Conversational Persuasion of LLM, Human-Computer Interaction, Behavioral Science, Large Language Models
Discipline: Behavioral Science
GPT-4 can use personalized arguments to be more persuasive in debates, outperforming humans in 64.4% of AI-human comparisons when personalization is applied.
Methods: Preregistered controlled study involving multiround debates with random assignment to conditions focusing on AI-human comparisons, personalization, and opinion strength.
Key Findings: Effectiveness of persuasion by GPT-4, especially when using personalized arguments, compared to humans in debates.
Citations: 65
Sample Size: 900
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Authors: F Salvi, MH Ribeiro, R Gallotti
Year: 2024
Published in: arXiv preprint arXiv ..., 2024 - atelierdesfuturs.org
Institution: EPFL, Fondazione Bruno Kessle
Research Area: Conversational Persuasion in LLM
Discipline: Artificial Intelligence
The study demonstrates that GPT-4 is highly persuasive in direct conversations, especially when equipped with personalized sociodemographic information about its opponent, raising concerns about its potential misuse in personalized persuasion contexts.
Methods: Participants engaged in multiple-round debates on a web-based platform under randomized conditions, with comparisons between human-human and human-AI interactions and the impact of personalization.
Key Findings: The persuasiveness of GPT-4 compared to humans, with and without personalization using sociodemographic data.
Citations: 118
Sample Size: 820
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Authors: D Testa, G Bonetta, R Bernardi
Year: 2024
Published in: Proceedings of the ..., 2025 - aclanthology.org
Institution: Università di Roma La Sapienza, Fondazione Bruno Kessler, University of Pisa
Research Area: Multimodal AI Assessment, Visual Language Models (VLMs), Video Understanding, Computational Linguistics
Discipline: Artificial Intelligence, Computational Linguistics
