5 papers
CriticaLLM: Using LLMs as Autonomous Game Master for Tabletop Role-Playing Games
Gaëtan Berlaimont, Justin Vanwichelen, Benoît Ronval +1
Large Language Models (LLMs) have shown impressive capabilities across many tasks, including processing large amounts of text, following instructions, and generating ideas. This al…
WIDER-FAIR: An Annotated Version of the WIDER-FACE Dataset for Fairness Evaluation
Maxime Moussi, Benoît Ronval, Siegfried Nijssen +1
The deployment of face detection models in real-world applications raises important fairness concerns, as these systems may showcase performance disparities across demographic grou…
TABFAIRGDT: A Fast Fair Tabular Data Generator using Autoregressive Decision Trees
Emmanouil Panagiotou, Benoît Ronval, Arjun Roy +4
Ensuring fairness in machine learning remains a significant challenge, as models often inherit biases from their training data. Generative models have recently emerged as a promisi…
TAGAL: Tabular Data Generation using Agentic LLM Methods
Benoît Ronval, Pierre Dupont, Siegfried Nijssen
The generation of data is a common approach to improve the performance of machine learning tasks, among which is the training of models for classification. In this paper, we presen…
Codenames as a Benchmark for Large Language Models
Matthew Stephenson, Matthew Sidji, Benoît Ronval
In this paper, we propose the use of the popular word-based board game Codenames as a suitable benchmark for evaluating the reasoning capabilities of Large Language Models (LLMs).…