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With the rise of generative AI, a new generation of intelligent phishing has emerged, where attackers leverage Large Language Models (LLMs) to craft websites with high semantic plausibility, posing critical challenges to...

IntroductionThe proliferation of generative artificial intelligence (AI) has created unprecedented opportunities for informal second language (L2) learning, yet the psychological mechanisms through which AI-mediated lear...

This article explores student equity in higher education through the lens of academic language and learning (ALL) and argues that ALL remains a significant barrier to participation and success for students from equity ba...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...

Current watermarking approaches for LLM-generated text typically embed watermarks during the generation process, using a secret key controlled by the LLM. Although this enables verification of LLM-generated content, it m...

Materias / palabras clave: antisemitism; artificial intelligence; digital communication; discourse analysis; hate speech; large language models

Language and action systems are functionally coupled in the brain as demonstrated by converging evidence using Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), transcranial magnetic stimulation...

Artificial intelligence (AI) technologies are being deeply integrated into critical infrastructures, making AI resilience essential to ensuring the secure and stable operation of such systems. This study defines AI resil...

Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

Abstract Cross-lingual information retrieval limits global exchange of data because of the high diversity in the methods to classify, document and encode medical procedures. Traditional keyword-based or single-language s...

Column type annotation (CTA) is a critical task in semantic table interpretation (STI), where meaningful semantic labels are automatically assigned to table columns. This process enriches tabular data with essential sema...

This study investigates whether a culturally immersive pedagogy can measurably enhance advanced Arabic speaking proficiency among non-native learners within the CEFR framework. Using a quasi-experimental design at King S...

Malware represents the most critical threat in cybersecurity, meant to compromise the security for any individual or any organization. These are covert software, designed to perform malicious act like data theft, data al...

ARM-based systems are widely deployed in edge and IoT settings, where penetration-testing tools must operate under strict memory, power, and thermal constraints, yet prior work offers limited deployment-oriented guidance...

This research paper examines ChatGPT's methodologies for addressing the untranslatability challenges posed by verbified proper nouns in English-Arabic translation. The process of denominalization, whereby proper nouns ar...

Digital Twin Networks (DTNs) are emerging as a key enabler for the robust optimization and lifecycle management of next-generation networks. However, current DTN approaches still rely heavily on manual design, implementa...

La evaluación de gran cantidad de exámenes de tipo respuesta abierta es una tarea docente que requiere de una elevada inversión de tiempo para su realización, presentando además otros importantes problemas y desafí...

Artificial intelligence (AI), including machine learning, deep learning, reinforcement learning, and generative AI, has the potential to advance critical care nephrology (CCN) by enhancing prediction accuracy, improving ...

Abstracts Alert fatigue remains a major barrier to the effective deployment of predictive models in emergency care, particularly in the context of rare but critical outcomes such as in-hospital mortality (IHM), which oft...

Artificial intelligence (AI) has emerged as a transformative force in modern ophthalmology, enabling rapid advances in disease detection, clinical decision support, workflow optimization, and tele-ophthalmology. Ophthalm...

Aims/objectives: This study aimed to evaluate the performance of leading large language models (LLMs) in orthopedic surgery, with a focus on diagnostic accuracy, radiographic interpretation, subspecialty-specific perform...

IntroductionThis article investigates the linguistic and computational challenges of detecting antisemitism in digital communication, integrating discourse-analytical and artificial intelligence (AI) perspectives. It con...

The development goal of artificial intelligence is to enable machines to think and act like humans, solving complex problems, and more importantly, interacting effectively in a complex, dynamic, and uncertain physical wo...