7 papers
The Power of Backdoor Absorption in Community Training
Issam Seddik, Sami Souihi, Mohamed Tamaazousti +1
Backdoor attacks severely threaten large-scale AI models. When model owners delegate training to external compute providers within a decentralized training paradigm, adversaries ca…
Certification and Classification of Linear Quantum Error Mitigation Methods
Zach Blunden-Codd, Mohamed Tamaazousti
Numerous mitigation methods exist for quantum noise suppression, making it challenging to identify the optimum approach for a specific application; especially as ongoing advances i…
Quantum error mitigation by hierarchy-informed sampling: chiral dynamics in the Schwinger model
Theo Saporiti, Oleg Kaikov, Vasily Sazonov +1
Quantum simulations on current NISQ hardware are limited by its noisy nature, making efficient quantum error mitigation methods highly demanded. In this paper we introduce a novel…
PoTS: Proof-of-Training-Steps for Backdoor Detection in Large Language Models
Issam Seddik, Sami Souihi, Mohamed Tamaazousti +1
As Large Language Models (LLMs) gain traction across critical domains, ensuring secure and trustworthy training processes has become a major concern. Backdoor attacks, where malici…
BBGKY hierarchy for quantum error mitigation
Theo Saporiti, Oleg Kaikov, Vasily Sazonov +1
Mitigation of quantum errors is critical for current NISQ devices. In the present work, we address this task by treating the execution of quantum algorithms as the time evolution o…
Quantum Error Mitigation by Global Randomized Error Cancellation for Adiabatic Evolution in the Schwinger Model
Oleg Kaikov, Theo Saporiti, Vasily Sazonov +1
We extend the global randomized error cancellation (GREC) method for quantum error mitigation (QEM) in an application to adiabatic evolution of states on a noisy quantum device. We…