activity
20242026
collaborators

5 papers

cs.LG2026

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences

Gurvan Richardeau, Gohar Dashyan, Erwan Le Merrer +1

Literature reveals that a Large Language Model's (LLM) behavior is not only conditioned by its original weights but also its instance-level parameters, such as instructional prompt…

cs.LG2025

Robust ML Auditing using Prior Knowledge

Jade Garcia Bourrée, Augustin Godinot, Martijn De Vos +5

Among the many technical challenges to enforcing AI regulations, one crucial yet underexplored problem is the risk of audit manipulation. This manipulation occurs when a platform d…

cs.CL2025

LLMs Prompted for Graphs: Hallucinations and Generative Capabilities

Gurvan Richardeau, Samy Chali, Erwan Le Merrer +2

Large Language Models (LLMs) are nowadays prompted for a wide variety of tasks. In this article, we investigate their ability in reciting and generating graphs. We first study the…

cs.LG2025

P2NIA: Privacy-Preserving Non-Iterative Auditing

Jade Garcia Bourrée, Hadrien Lautraite, Sébastien Gambs +3

The emergence of AI legislation has increased the need to assess the ethical compliance of high-risk AI systems. Traditional auditing methods rely on platforms' application program…

cs.LG2024

Queries, Representation & Detection: The Next 100 Model Fingerprinting Schemes

Augustin Godinot, Erwan Le Merrer, Camilla Penzo +2

The deployment of machine learning models in operational contexts represents a significant investment for any organisation. Consequently, the risk of these models being misappropri…