Synthetic Is All You Need: Removing the Auxiliary Data Assumption for Membership Inference Attacks Against Synthetic Data. - Florent Guépin; Matthieu Meeus; Ana-Maria Cretu 002; Yves-Alexandre de Montjoye (ESORICS Workshops (1), 2023)

Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing. - Matthieu Meeus; Florent Guépin; Ana-Maria Cretu 002; Yves-Alexandre de Montjoye (ESORICS (2), 2023)

Copyright Traps for Large Language Models. - Matthieu Meeus; Igor Shilov; Manuel Faysse; Yves-Alexandre de Montjoye (ICML, 2024)

Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models. - Matthieu Meeus; Shubham Jain; Marek Rei; Yves-Alexandre de Montjoye (USENIX Security Symposium, 2024)

Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models. - Florent Guépin; Natasa Krco; Matthieu Meeus; Yves-Alexandre de Montjoye (CoRR, 2024)

Mosaic Memory: Fuzzy Duplication in Copyright Traps for Large Language Models. - Igor Shilov; Matthieu Meeus; Yves-Alexandre de Montjoye (CoRR, 2024)

Inherent Challenges of Post-Hoc Membership Inference for Large Language Models. - Matthieu Meeus; Shubham Jain; Marek Rei; Yves-Alexandre de Montjoye (CoRR, 2024)

ChocoLlama: Lessons Learned From Teaching Llamas Dutch. - Matthieu Meeus; Anthony Rathé; François Remy; Pieter Delobelle; Jens-Joris Decorte; Thomas Demeester (CoRR, 2024)

SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It). - Matthieu Meeus; Igor Shilov; Shubham Jain; Manuel Faysse; Marek Rei; Yves-Alexandre de Montjoye (SaTML, 2025)

The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text. - Matthieu Meeus; Lukas Wutschitz; Santiago Zanella-Béguelin; Shruti Tople; Reza Shokri (CoRR, 2025)

Alignment Under Pressure: The Case for Informed Adversaries When Evaluating LLM Defenses. - Xiaoxue Yang; Bozhidar Stevanoski; Matthieu Meeus; Yves-Alexandre de Montjoye (CoRR, 2025)

Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models. - Jamie Hayes; Ilia Shumailov; Christopher A. Choquette-Choo; Matthew Jagielski; Georgios Kaissis; Katherine Lee; Milad Nasr; Sahra Ghalebikesabi; Niloofar Mireshghallah; Meenatchi Sundaram Mutu Selva Annamalai; Igor Shilov; Matthieu Meeus; et al. (CoRR, 2025)

Counterfactual Influence as a Distributional Quantity. - Matthieu Meeus; Igor Shilov; Georgios Kaissis; Yves-Alexandre de Montjoye (CoRR, 2025)