Related papers: Development of an Autonomous Detection-Unit Self-T…

Instance object detection plays an important role in intelligent monitoring, visual navigation, human-computer interaction, intelligent services and other fields. Inspired by the great success of Deep Convolutional Neural Network (DCNN),…

With the rapid progress of large language models (LLMs) and the huge amount of text they generated, it becomes more and more impractical to manually distinguish whether a text is machine-generated. Given the growing use of LLMs in social…

Natural radioactivity represents one of the main backgrounds in the search for neutrinoless double beta decay. Within the NEXT physics program, the radioactivity-induced backgrounds are measured with the NEXT-White detector. Data from 37.9…

We present the preparation, deployment, and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS experiment Global Trigger (GT) test crate FPGAs during LHC Run 3. The GT makes the final decision…

This study evaluates the ability of GPT-4o to autonomously solve beginner-level offensive security tasks by connecting the model to OverTheWire's Bandit capture-the-flag game. Of the 25 levels that were technically compatible with a…

Large language model (LLM) has achieved promising performance in multilingual machine translation tasks through zero/few-shot prompts or prompt-tuning. However, due to the mixture of multilingual data during the pre-training of LLM, the…

The goal of our study is to assess the environmental impact of the installation and use of the Giant Radio Array for Neutrino Detection (GRAND) prototype detection units, based on the life cycle assessment (LCA) methodology, and to propose…

The GERmanium Detector Array (GERDA) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta ($0\nu\beta\beta$) decay of $^{76}$Ge. The technological challenge of GERDA is to operate in a…

Automating penetration testing is crucial for enhancing cybersecurity, yet current Large Language Models (LLMs) face significant limitations in this domain, including poor error handling, inefficient reasoning, and an inability to perform…

While Large Language Models (LLMs) demonstrate remarkable capabilities, they remain susceptible to sophisticated, multi-step jailbreak attacks that circumvent conventional surface-level safety alignment by exploiting the internal generation…

This manuscript describes an innovative method to tag the muons using the baseline information of the Flash ADC (FADC) waveform of PMTs in the JSNS1 (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) experiment. This…

In the monitoring of a complex electric grid, it is of paramount importance to provide operators with early warnings of anomalies detected on the network, along with a precise classification and diagnosis of the specific fault type. In this…

The trigger system for the Auger fluorescence telescopes is implemented in hard- and software for an efficient selection of fluorescence light tracks induced by high-energy extensive air showers. The algorithm of the third stage uses the…

Future large liquid-scintillator (LS) detectors are competitive with and complementary to the water-Cherenkov detectors on the searches for diffuse supernova neutrino background and nucleon decay. In a companion paper, we have performed a…

In this work we analyse the ultimate sensitivity of dark matter direct detection experiments, the "neutrino-floor", in the presence of anomalous sources of dark radiation in form of SM or semi-sterile neutrinos. This flux-component is…

Infrared search and tracking (IRST) system has been widely concerned and applied in the area of national defence. Small target detection under complex background is a very challenging task in the development of system algorithm. Low…

Highly selective triggers are essential for the physics programme of the ATLAS experiment at HL-LHC where the instantaneous luminosity will be about an order of magnitude larger than the LHC instantaneous luminosity in Run 1. The first…

Low Temperature Detectors (LTDs) offer the best signal-to-noise performance and thus, lowest energy threshold among other particle detection technologies available today. The excellent background rejection provided by these detectors is…

Large Language Models (LLMs) have achieved remarkable performance across diverse tasks, yet their susceptibility to generating incorrect content during inference remains a critical unsolved challenge. While self-correction methods offer…

This paper presents an innovative exploration of the application potential of large language models (LLM) in addressing the challenging task of automatically generating behavior trees (BTs) for complex tasks. The conventional manual BT…