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Traditional travel surveys are costly, time-consuming and face declining response rates, motivating the exploration of artificial data generation methods. In this research, we propose a novel Persona-Driven Method (PDM) ...

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...

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...

To ensure safe driving in dynamic environments, autonomous vehicles should possess the capability to accurately predict lane change intentions of surrounding vehicles in advance and forecast their future trajectories. Ex...

Automatic differentiation (AD) enables powerful metasurface inverse design but requires extensive theoretical and programming expertise. We present a Model Context Protocol (MCP) assisted framework that allows researcher...

Tuberculosis (TB) vaccine design relies on the selection of optimal antigens. However, evidence on candidate antigens is scattered across the literature and rarely linked to critical vaccine parameters, such as immune re...

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...

In recent years, Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) have gained significant momentum in the automation of software development. Although, previous research studies have also explo...

Large language models (LLMs) are rapidly pushing the limits of contemporary computing hardware. For example, training GPT-3 has been estimated to consume around 1,300 MWh of electricity, and projections suggest future ...

The Smart Building paradigm promises a future where buildings are intelligent, adaptive, and sustainable, offering real-time information retrieval that supports decision-making to enhance energy efficiency, occupant comf...

The United States Immunodeficiency Network (USIDNET) is a registry that collects de-identified patient data from hospitals across the country to study rare immune conditions, including inborn errors of immunity (IEI). Th...

Abstract Research in power system is persistently hampered by the scarcity of high‐fidelity, public grid data due to security and privacy constraints. Existing unimodal synthesis methods fail to harmonize physical laws...

Introduction and aims: To evaluate the diagnostic and reasoning capabilities of 4 state-of-the-art large language models (LLMs) on the Korean Dental Licensing Examination (KDLE) and to assess their potential as education...

Abstract: This study investigates an approach to test a key requirement for using large language models (LLMs) to simulate valid data sets of item-responses, namely the effect of trait induction on another related constr...

Importance Emergency departments (EDs) face significant documentation burdens due to reliance on unstructured clinical narratives, hindering efficiency, particularly in pediatric care. Large language models (LLMs) offer ...

Abstract Historical analogies recur in leaders’ discourse during crises as policymakers rely on familiar frameworks to navigate complex foreign-policy decisions and to create a sense of continuity amid unprecedented ch...

Optimizing modern factories requires dynamic, data-driven decision support aligned with Industry 5.0’s human-centric principles. This research introduces the ‘immersive cognitive factory twin’, a novel framework le...

This paper presents an exploratory case study detailed as a pedagogical experience report on integrating adversarial Large Language Model (LLM) scenarios into a graduate cybersecurity curriculum. In addition to prompt in...

Despite the impressive strides of large language models (LLMs) in text summarization, their effectiveness still hinges on well-crafted prompts, a process that remains labor-intensive, subjective, and difficult to scale. ...

Water information systems (ISs) are essential for sustainable water management but are often constrained by fragmented, heterogeneous, and rapidly evolving data. Advances in generative artificial intelligence (GenAI), pa...

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...

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...

Urban transportation systems are rapidly evolving into CPSS (cyber-physical-social system), driven by the continuous integration of autonomous vehicles, unmanned aerial vehicles, and diverse intelligent agents. This evol...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...