13 citations · 21 across the 5 of their papers we have counts for
5 papers
Are LLMs ready to help non-expert users to make charts of official statistics data?
Gadir Suleymanli, Alexander Rogiers, Lucas Lageweg +1
In this time when biased information, deep fakes, and propaganda proliferate, the accessibility of reliable data sources is more important than ever. National statistical institute…
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…
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…
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…
KamerRaad: Enhancing Information Retrieval in Belgian National Politics through Hierarchical Summarization and Conversational Interfaces
Alexander Rogiers, Maarten Buyl, Bo Kang +1
KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information. The tool extracts and concisely summarizes ke…