80 citations · 182 across the 20 of their papers we have counts for
5 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…
ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods
MaryBeth Defrance, Maarten Buyl, Tijl De Bie
Numerous methods have been implemented that pursue fairness with respect to sensitive features by mitigating biases in machine learning. Yet, the problem settings that each method…
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…
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms
Raphaël Romero, Maarten Buyl, Tijl De Bie +1
Dynamic Link Prediction (DLP) addresses the prediction of future links in evolving networks. However, accurately portraying the performance of DLP algorithms poses challenges that…
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…