The use of large language models (LLMs) is now spreading in several areas of research and development. This work is concerned with systematically reviewing LLMs’ involvement in engineering education. Starting from a general research question, t...
Requirements Engineering and Management (REM) tools play a significant role in ensuring project compliance and efficiency. Automotive engineering must comply with regulatory standards, requiring detailed documentation, rigorous testing, and solid tra...
Although recent years have seen an emergence of tools for automated identification of deceptive design patterns on websites, their scope and reliability remain understudied. Institutional websites are a particularly interesting research domain. They...
The rapid expansion of large language models (LLMs) has created new opportunities for university mental health services, particularly in contexts where counseling demand exceeds available professional resources. This study examined the application of...
Self-regulated learning (SRL) is a sustainable development skill that involves learners actively monitoring and adjusting their learning processes, which is essential for lifelong learning. Learning feedback plays a crucial role in SRL by aiding in s...
Objective: Large Language Models (LLMs) are emerging as a key component for digital health systems based on Artificial Intelligence (AI). The objective of this paper is to systematically review the characteristics, effectiveness, and implementation c...
Access to practice opportunities for history-taking in undergraduate medical education can be resource-limited. Large language models are a potential avenue to address this. This study sought to characterize changes in learner self-reported confidenc...
As large language models (LLMs) are increasingly used to support learning, there is a growing need for a principled framework to guide the design of LLM-based tools and resources that are pedagogically effective and contextually responsive. This stud...
Large language models (LLMs) are increasingly integrated into interactive systems across domains such as software development, robotics, and education. As these systems evolve from simple chat interfaces to autonomous, tool-using agents, the design o...
The purpose of this research is to systematically map and analyze the use of AI technologies in project management, identifying themes, research gaps, and practical implications. This study conducts a systematic literature review (SLR) that combines...
Agent-based modeling (ABM) is a powerful tool for simulating building users’ dynamic behavior in demand response (DR) programs. However, ABM faces several challenges, particularly in encoding building users’ natural language features and...
The proliferation of fake news and fake profiles on social media platforms poses significant threats to information integrity and societal trust. Traditional detection methods, including rule-based approaches, metadata analysis, and human fact-checki...
Large Language Models (LLMs) are emerging as powerful tools for automating business process modeling, promising to streamline the translation of textual process descriptions into Business Process Model and Notation (BPMN) diagrams. However, the exten...
Urban air mobility (UAM) introduces electric vertical takeoff and landing (eVTOL) systems, creating new requirements for infrastructure planning. Vertiport siting is central, yet existing approaches such as multi-criteria decision analysis and optimi...
Identifying network protocol vulnerabilities is critical for cyberspace security. Generation-based black-box protocol fuzzing is widely used but faces challenges: over-reliance on manual protocol analysis and script writing, single-threaded fuzzing,...
Labour markets across Europe increasingly describe workers through skills rather than job titles, and a growing number of large language model (LLM)-based tools now claim to extract these skills automatically from unstructured text at scale. Among th...
The convergence of Large Language Models (LLMs) and Internet of Things (IoT) systems has created a new class of intelligent applications across healthcare, industrial automation, smart cities, and connected homes. However, this integration introduces...
This study investigates the effects of LLM-based coding assistance on web application development by students using a frontend framework. Rather than comparing different models, it focuses on how students interact with LLM tools to isolate the impact...
Background: The implementation of Large Language Models (LLMs) in software engineering has provided new and improved approaches to code synthesis, testing, and refactoring. However, even with these new approaches, the practical efficacy of LLMs is re...
Recent research on web accessibility has explored the use of artificial intelligence (AI), particularly large language models (LLMs), to support accessibility remediation. However, the field lacks a theoretical perspective explaining how LLMs can be...
Historical document collections are increasingly available as digitised images and PDFs, but their conversion into reliable text remains affected by optical character recognition (OCR) errors, degraded pages, heterogeneous layouts, and domain-specifi...
Contractual agreements often contain clauses that are unfair, creating unjust suffering in one party to the agreement. ContractNerd leverages advanced Large Language Models (LLMs) to analyze contractual agreements and identify issues across four cate...
Automated test case generation aims to improve software testing by reducing the manual effort required to create test cases. Recent advancements in large language models (LLMs), with their ability to understand natural language and generate code, hav...
Large language model (LLM)-based multi-agent systems are increasingly being explored as tools for supporting structured collective decision-making, but it remains unclear how the diversity structure of agent groups affects decision-making performance...
The acquisition of cybersecurity threat intelligence is a critical task in the implementation of effective security defense strategies. Recently, advancements in large language model (LLM) technology have led to remarkable capabilities in natural lan...
Large language model (LLM)-based agents are rapidly emerging as transformative tools across biomedical research and clinical applications. By integrating reasoning, planning, memory, and tool use capabilities, these agents go beyond static language m...
Flood risk maps play a critical role in land-use regulation, infrastructure planning, and community preparedness, which are key components of sustainable and climate-resilient urban development. Their production, however, remains costly, labor-intens...
Biological-sequence representation methods are pivotal for advancing machine learning in computational biology, transforming nucleotide and protein sequences into formats that enhance predictive modeling and downstream task performance. This review c...
Large Language Models (LLMs) are increasingly proposed to personalize healthcare delivery, yet their real-world readiness remains uncertain. We conducted a systematic literature review to assess how LLM-based systems are designed and used to enhance...
Large language models (LLMs) show limited capability in processing low-resource historical languages due to insufficient training data and domain-specific linguistic structures. Korean Literary Sinitic (KLS), the principal written medium of the Joseo...
The maturation of internet usage environments has elevated User Experience (UX) to a critical factor in system success. However, traditional manual UX testing methods are hampered by subjectivity and lack of standardization, resulting in time-consumi...
The exponential growth of biomedical literature necessitates advanced methods for Literature-Based Discovery (LBD) to uncover hidden, meaningful relationships and generate novel hypotheses. This research integrates Large Language Models (LLMs), parti...
Adverse drug events (ADEs) significantly impact patient safety and health outcomes. Manual ADE detection from clinical narratives is time-consuming, labor-intensive, and costly. Recent advancements in large language models (LLMs), including transform...
LLM-based systems used for tutoring can produce fluent and apparently plausible explanations, but they do not guarantee Technical Correctness, which is paramount in STEM fields such as Electrical Circuit Analysis. This study investigates how three LL...
Large Language Models (LLMs) are emerging as a new class of intelligent systems capable of reasoning over heterogeneous knowledge and interacting with human operators, yet their role in renewable energy systems remains insufficiently synthesized. Thi...
Background/Objectives: Children with autism spectrum disorder (ASD) commonly experience feeding- and nutrition-related problems, while families increasingly encounter large language model (LLM)-based tools as sources of health information. Evidence o...
Large Language Model (LLM)-based agents automate complex tasks by integrating external tools such as web browsers, e-mail clients, file readers, and APIs, but this same integration exposes them to indirect prompt injection (IPI) attacks, in which mal...
Programmable Logic Controllers (PLCs), widely used in industrial automation, are often programmed in IEC 61131-3 Structured Text (ST), which is prone to subtle logic vulnerabilities. Traditional tools like static analysis and fuzzing struggle with th...
This paper explores the emerging potential of large language models (LLMs) and generative AI for social network analysis (SNA) based on open-ended survey data as a source. We introduce a novel methodology, Survey-to-Multilayer Network (SURVEY2MLN), w...
Introduction: Mass casualty incident (MCI) simulation scenarios are developed based on detailed review and planning by multidisciplinary trauma teams. This study aimed to assess the feasibility of using generative artificial intelligence (AI) in deve...
This study examines the perceived and actual effectiveness of an LLM-driven tutor embedded in an educational game for Chinese as a foreign language (CFL) learners. Drawing on 82 chat sessions from 31 beginner-level (HSK3) CFL learners, we analyzed le...
Reservoir simulation is an important technique to characterize subsurface fluid flow and to support reservoir development and production optimization. Conventional reservoir modeling requires engineers to extract model-relevant information from heter...
The reciprocal relationship between large language models (LLMs) and knowledge graphs (KGs) opens new opportunities for knowledge discovery from scientific literature; however, most approaches address only one direction of this interaction. In comple...
As Large Language Models (LLMs) are core components in Retrieval-Augmented Generation (RAG) systems for knowledge-intensive tasks, concerns regarding hallucinations, redundancy, and unverifiable outputs have intensified, particularly in high-stakes d...
Large language models (LLMs) are increasingly useful as front-end tools for decision support, particularly when extensive textual reports must be read and transformed into a structured analytical form. However, summarisation and decision making are d...
Background: The Spinal Instability Neoplastic Score (SINS) guides treatment for patients with spinal tumors, but issues arise with complexity, interobserver variability, and time demands. Large language models (LLMs) may help overcome these limitatio...
This work proposes a general conceptual framework for integrating TRIZ (Theory of Inventive Problem Solving) structured reasoning into large language model (LLM)-based workflows for chemical and materials science. We argue that persistent AI challeng...
Large Language Models (LLMs) have emerged as powerful tools in cyber security, enabling automation, threat detection, and adaptive learning. Their ability to process unstructured data and generate context-aware outputs supports both operational tasks...
Large language models (LLMs) have emerged as powerful tools for (semi-)automating the initial screening of abstracts in systematic reviews, offering the potential to significantly reduce the manual burden on research teams. This paper provides a broa...
(1) Background/Objectives: Over one billion individuals globally live with mental health conditions, yet the treatment gap exceeds 75% in low- and middle-income countries. Large language model (LLM)-based conversational agents have emerged as a poten...
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