4 papers · 1 filter
Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implications
Sander Noels, Alexander Rogiers, Maarten Buyl +1
The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive conten…
VIGIL: An Extensible System for Real-Time Detection and Mitigation of Cognitive Bias Triggers
Bo Kang, Sander Noels, Tijl De Bie
The rise of generative AI is posing increasing risks to online information integrity and civic discourse. Most concretely, such risks can materialise in the form of mis- and disinf…
What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices
Sander Noels, Guillaume Bied, Maarten Buyl +4
Large Language Models (LLMs) are increasingly deployed as gateways to information, yet their content moderation practices remain underexplored. This work investigates the extent to…
Large Language Models Reflect the Ideology of their Creators
Maarten Buyl, Alexander Rogiers, Sander Noels +8
Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These…