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Context presentation and native conversation structure in large language model responses to escalating suicide risk: a controlled multimodel evaluation

Jueqiao Liu, Jueqiao Liu, Xiaoyi Chen, Jun Cai et al. • Frontiers in Psychiatry (2026)

BackgroundLarge language models are increasingly used for informal mental health support, yet their safety during escalating suicide-risk conversations may depend on how prior information is presented. Native multi-turn conversations and re...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2026.1962098

System 2 Thinking in OpenAI’s o1-Preview Model: Near-Perfect Performance on a Mathematics Exam

Joost C. F. de Winter, Dimitra Dodou, Yke Bauke Eisma • Computers (2024)

The processes underlying human cognition are often divided into System 1, which involves fast, intuitive thinking, and System 2, which involves slow, deliberate reasoning. Previously, large language models were criticized for lacking the de...

DOAJ Open Access (DOAJ) DOI: 10.3390/computers13110278

Comparative assessment of patient education content generated by five large language models on post-stroke complications: A cross-sectional study of safety, accuracy, reliability, readability, and empathy

Long-Xian Liu, Huan-Huan Wang, Shuang Lu, Guo Yu et al. • Digital Health (2026)

Objective To compare the safety, accuracy, reliability, readability, and empathy of patient education content generated by five large language models (LLMs) for post-stroke complications. Methods This CHART-guided cross-sectional comparativ...

DOAJ Open Access (DOAJ) DOI: 10.1177/20552076261493266

Evaluating an LLM-assisted workflow for clinical documentation: A pilot randomized controlled trial on time and quality.

Tomohiro Takayama, Keina Sado, Kenji Suda, Hiroshi Tamura et al. • PLOS Digital Health (2026)

Large language models (LLMs) have been investigated for clinical documentation, with concerns about hallucinations and factual errors. Clinician review and revision of LLM-generated drafts are considered essential; however, the impact of su...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pdig.0001799

Comparative Analysis of Deep Natural Networks and Large Language Models for Aspect-Based Sentiment Analysis

Nimra Mughal, Ghulam Mujtaba, Sarang Shaikh, Aveenash Kumar et al. • IEEE Access (2024)

Sentiment analysis is essential for comprehending public opinion, particularly when considering e-commerce and the expansion of online businesses. Early approaches treated sentiment analysis as a document or sentence-level classification pr...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3386969

Interaction with LLM-Based Systems: A Structured Review and Taxonomy of Mechanisms and Autonomy

Dino Nejašmić, Saša Mladenović, Andrina Granić • Applied Sciences (2026)

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, th...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16105001

Synergizing Generative AI and Cybersecurity: Roles of Generative AI Entities, Companies, Agencies, and Government in Enhancing Cybersecurity

Pan Singh Dhoni, Ravinder Kumar (2023)

The digital landscape of the modern world has witnessed a remarkable evolution over the past few decades, with technological advancements permeating every facet of our lives. While these innovations have brought forth unprecedented convenie...

OPENALEX cc-by DOI: https://doi.org/10.36227/techrxiv.23968809.v1

Review of Generative AI methods in cybersecurity

Yagmur Yigit, William Johnston Buchanan, Madjid Tehrani, Leandros A. Maglaras • Internet of Things and Cyber-Physical Systems (2025)

Over the last decade, Artificial Intelligence (AI) has become increasingly popular, especially with the use of chatbots such as ChatGPT, Google’s Gemini, and DALL-E. With this rise, large language models (LLMs) and Generative AI (GenAI) hav...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.iotcps.2026.04.001

Generative AI in cybersecurity: A comprehensive review of LLM applications and vulnerabilities

Mohamed Amine Ferrag, Fatima Alwahedi, Ammar Ayman Battah, Bilel Cherif et al. • Internet of Things and Cyber-Physical Systems (2025)

This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection, s...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.iotcps.2025.01.001

Large Language Models in Cybersecurity: State-of-the-Art

Farzad Nourmohammadzadeh Motlagh, Mehrdad Hajizadeh, Mehryar Majd, Pejman Najafi et al. • International Conference on Information Systems Security and Privacy (ICISSP) (2025)

The rise of Large Language Models (LLMs) has revolutionized our comprehension of intelligence bringing us closer to Artificial Intelligence. Since their introduction, researchers have actively explored the applications of LLMs across divers...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.5220/0013377600003899

Quantifying Gender Bias in Large Language Models Using Information-Theoretic and Statistical Analysis

Imran Mirza, Akbar Anbar Jafari, Cagri Ozcinar, Gholamreza Anbarjafari • Information (2025)

Large language models (LLMs) have revolutionized natural language processing across diverse domains, yet they also raise critical fairness and ethical concerns, particularly regarding gender bias. In this study, we conduct a systematic, mat...

DOAJ Open Access (DOAJ) DOI: 10.3390/info16050358

Applications of natural language processing and large language models in materials discovery

Xue Feng Jiang, Weiren Wang, Shaohan Tian, Hao Wang et al. • npj Computational Materials (2025)

The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered too...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1038/s41524-025-01554-0

AI-generated draft replies to patient messages: exploring effects of implementation

Charlotte M. H. H. T. Bootsma-Robroeks, Charlotte M. H. H. T. Bootsma-Robroeks, Jessica D. Workum, Jessica D. Workum et al. • Frontiers in Digital Health (2025)

IntroductionThe integration of Large Language Models (LLMs) in Electronic Health Records (EHRs) has the potential to reduce administrative burden. Validating these tools in real-world clinical settings is essential for responsible implement...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdgth.2025.1588143

Construction of a knowledge graph for the educational statistical indicator system based on large language models

WANG Pengyu, JIANG Shuming, WEI Zhiqiang, YU Jun, ZHANG Mengmeng • Shandong kexue (2026)

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

DOAJ Open Access (DOAJ) DOI: 10.3976/j.issn.1002-4026.2025079

DEVELOPMENT OF A QUESTION ANSWERING CHATBOT FOR BLOCKCHAIN DOMAIN

Aigerim Mansurova, Aliya Nugumanova, Zhansaya Makhambetova • Scientific Journal of Astana IT University (2023)

Large Language Models (LLMs), such as ChatGPT, have transformed the field of natural language processing with their capacity for language comprehension and generation of human-like, fluent responses for many downstream tasks. Despite their ...

DOAJ Open Access (DOAJ) DOI: 10.37943/15XNDZ6667

Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies

Andrea Cadeddu, Alessandro Chessa, Vincenzo De Leo, Gianni Fenu et al. • Information (2024)

Online platforms have become the primary means for travellers to search, compare, and book accommodations for their trips. Consequently, online platforms and revenue managers must acquire a comprehensive comprehension of these dynamics to f...

DOAJ Open Access (DOAJ) DOI: 10.3390/info15070398

Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen et al. • Conference on Empirical Methods in Natural Language Processing (EMNLP) (2023)

Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot-i.e., without adaptation on downstream data.Recently, the debut of ChatGP...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2023.emnlp-main.85