Guillaume Bied

According to our database, Guillaume Bied authored at least 9 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Building and Measuring Trust between Large Language Models.

Maarten Buyl, Yousra Fettach, Guillaume Bied, Tijl De Bie

CoRR, August, 2025

BiMi Sheets: Infosheets for bias mitigation methods.

MaryBeth Defrance, Guillaume Bied, Maarten Buyl, Jefrey Lijffijt, Tijl De Bie

CoRR, May, 2025

Fifth Workshop on Recommender Systems for Human Resources (RecSys in HR 2025).

Toine Bogers, Mesut Kaya, Jens-Joris Decorte, Chris Johnson, Guillaume Bied

Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices.

Sander Noels, Guillaume Bied, Maarten Buyl, Alexander Rogiers, Yousra Fettach, Jefrey Lijffijt, Tijl De Bie

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

InfoClus: Informative Clustering of High-Dimensional Data Embeddings.

Fuyin Lai, Edith Heiter, Guillaume Bied, Jefrey Lijffijt

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

2024

Designing Recommender Systems for the Labor Market. (Concevoir et évaluer les algorithmes de recommandation pour le marché du travail).

Guillaume Bied

PhD thesis, 2024

2023

Toward Job Recommendation for All.

Guillaume Bied, Solal Nathan, Elia Perennes, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Christophe Gaillac, Michèle Sebag

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

RECTO : REcommandation diminuant la Congestion par Transport Optimal.

Guillaume Bied, Elia Perennes, Solal Nathan, Victor Naya, Philippe Caillou, Bruno Crépon, Christophe Gaillac, Michèle Sebag

Proceedings of the 9ème Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle, 2023

Fairness in job recommendations: estimating, explaining, and reducing gender gaps.

Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Solal Nathan, Michèle Sebag

Proceedings of the 1st Workshop on Fairness and Bias in AI co-located with 26th European Conference on Artificial Intelligence (ECAI 2023), 2023