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Software vulnerabilities continue to be ubiquitous, even in the era of AI-powered code assistants, advanced static analysis tools, and the adoption of extensive testing frameworks. It has become apparent that we must not simply prevent…
The task of identifying B meson flavor at the primary interaction point in the LHCb detector is crucial for measurements of mixing and time-dependent CP violation. Flavour tagging is usually done with a small number of expert systems that…
Standard single-turn, static benchmarks fall short in evaluating the nuanced capabilities of Large Language Models (LLMs) on complex tasks such as software engineering. In this work, we propose a novel interactive evaluation framework that…
A Geant4 based simulation tool has been developed to perform Monte Carlo modelling of a 6 MV VarianTM iX clinac. The computer aided design interface of Geant4 was used to accurately model the LINAC components, including the Millenium…
This note gives a conceptual description and illustration of the CLD detector, based on the work for a detector at CLIC. CLD is one of the detectors envisaged at a future 100 km $e^+e^-$ circular collider (FCC-ee). The note also contains a…
DEPFET active pixel sensors are a well-developed technology for vertex detectors at future colliders. Extensive test beam campaigns have proven the excellent performance of these devices, and their radiation hardness has been thoroughly…
International Linear Collider (ILC) is a next-generation $e^+e^-$ linear collider to explore Beyond-Standard-Models by precise measurements of Higgs bosons. Jet flavor tagging plays a vital role in the ILC project by identification of $H\to…
With the rapid advancement of Multimodal Large Language Models (MLLMs), an increasing number of researchers are exploring their application in recommendation systems. However, the high latency associated with large models presents a…
With the HL-LHC upgrade of the LHC machine, an increase of the instantaneous luminosity by a factor of five is expected and the current detection systems need to be validated for such working conditions to ensure stable data taking. At the…
Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…
We present a novel method for local image feature matching. Instead of performing image feature detection, description, and matching sequentially, we propose to first establish pixel-wise dense matches at a coarse level and later refine the…
We propose a new sequential jet reconstruction algorithm for future lepton colliders at the energy frontier. The Valencia algorithm combines the natural distance criterion for lepton colliders with the greater robustness against backgrounds…
IFC data has become the general building information standard for collaborative work in the construction industry. However, IFC data can be very complicated because it allows for multiple ways to represent the same product information. In…
This paper describes the LPVcore software package for MATLAB developed to model, simulate, estimate and control systems via linear parameter-varying (LPV) input-output (IO), state-space (SS) and linear fractional (LFR) representations. In…
Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup expected from the High-Luminosity LHC, the computational…
Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrect action sequences. To address these limitations, we propose VeriGraph, a novel framework that…
The Compact Linear Collider, CLIC, is a multi-TeV electron-positron collider proposed for construction at CERN. A detector model, CLICdet, that is suited for the experimental conditions at CLIC and is based on realistic performance, has…
Charge Coupled Devices (CCDs) have been successfully used in several high energy physics experiments over the past two decades. Their high spatial resolution and thin sensitive layers make them an excellent tool for studying short-lived…
Machine Learning is a rapidly expanding field with a wide range of applications in science. In the field of physics, the Large Hadron Collider, the world's largest particle accelerator, utilizes Neural Networks for various tasks, including…
We present an integrated framework for using Convolutional Networks for classification, localization and detection. We show how a multiscale and sliding window approach can be efficiently implemented within a ConvNet. We also introduce a…