3 citations · 3 across the 5 of their papers we have counts for
5 papers
Influence Score and Transformers interpretability: Measure of the Effective Impact of Attention Heads at inference time
Lisa Bouger, Yannick Teglia, Philippe Loubet Moundi
We propose an influence score to quantify the contribution of attention heads to classification decisions in Transformer-based models designed for prompt injection detection. The s…
Backdoor Unlearning Generalization: A Path Toward the Removal of Unknown Triggers in LLMs
Lisa Bouger, Théo Lasnier, Philippe Loubet Moundi +2
Backdoor attacks in Large Language Models (LLMs) are a growing security concern, where models can generate adversary-chosen content. Existing defenses target backdoors one at a tim…
Backdoor Attacks on Deep Learning Face Detection
Quentin Le Roux, Yannick Teglia, Teddy Furon +1
Face Recognition Systems that operate in unconstrained environments capture images under varying conditions,such as inconsistent lighting, or diverse face poses. These challenges r…
SoK: On the Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems
Quentin Le Roux, Yannick Teglia, Teddy Furon +2
The widespread deployment of Deep Learning-based Face Recognition Systems raises many security concerns. While prior research has identified backdoor vulnerabilities on isolated co…
Backdoored Retrievers for Prompt Injection Attacks on Retrieval Augmented Generation of Large Language Models
Cody Clop, Yannick Teglia
Large Language Models (LLMs) have demonstrated remarkable capabilities in generating coherent text but remain limited by the static nature of their training data. Retrieval Augment…