papers

Publications (5)

cs.LG2025

Design Patterns for Securing LLM Agents against Prompt Injections

Luca Beurer-Kellner, Beat Buesser, Ana-Maria Creţu +11

As AI agents powered by Large Language Models (LLMs) become increasingly versatile and capable of addressing a broad spectrum of tasks, ensuring their security has become a critica…

quant-ph2021

Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction

Cenk Tüysüz, Carla Rieger, Kristiane Novotny +6

The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminos…

quant-ph2020

A Quantum Graph Neural Network Approach to Particle Track Reconstruction

Cenk Tüysüz, Federico Carminati, Bilge Demirköz +6

Unprecedented increase of complexity and scale of data is expected in computation necessary for the tracking detectors of the High Luminosity Large Hadron Collider (HL-LHC) experim…

quant-ph2020

Particle Track Reconstruction with Quantum Algorithms

Cenk Tüysüz, Federico Carminati, Bilge Demirköz +6

Accurate determination of particle track reconstruction parameters will be a major challenge for the High Luminosity Large Hadron Collider (HL-LHC) experiments. The expected increa…

quant-ph2021

Performance of Particle Tracking Using a Quantum Graph Neural Network

Cenk Tüysüz, Kristiane Novotny, Carla Rieger +7

The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminos…