activity
20242026
most citedUnder manipulations, are some AI models harder to audit?

2 citations · 3 across the 7 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

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.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★ 1 cited

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…

cs.LG2024★ 2 cited

Under manipulations, are some AI models harder to audit?

Augustin Godinot, Gilles Tredan, Erwan Le Merrer +2

Auditors need robust methods to assess the compliance of web platforms with the law. However, since they hardly ever have access to the algorithm, implementation, or training data…