Results 81 to 90 of about 3,227,651 (213)

Accuracy and Consistency of Artificial Intelligence Chatbots in Dental Anatomy Education: A Comparative Study

European Journal of Education, Volume 61, Issue 4, December 2026.
ABSTRACT The potential of Artificial Intelligence (AI), large language models (LLMs) in enhancing dental education emphasises the need for careful selection of AI tools to improve learning outcomes. Therefore, this study evaluates the accuracy and consistency of responses from eight AI chatbots to multiple‐choice questions (MCQs) related to dental ...
Mubashir Baig Mirza, Ali Robaian, Abdullah Saad Alqahtani, Abdullah A. Alqahtani, Khalid K. Alanazi, Mohammed A. S. Abuelqomsan, Shahad AlBader, Hamod Alqahtani, Abdullah AlShehri   +8 more
wiley   +1 more source

ArGemma: A Multi‐Task Fine‐Tuning Framework for Adapting Gemma to Arabic

Expert Systems, Volume 43, Issue 11, November 2026.
ABSTRACT Open‐source large language models (LLMs) have significantly advanced natural language processing (NLP), particularly for English. However, their performance in Arabic has remained limited due to the scarcity of high‐quality datasets and the high computational cost of full fine‐tuning.
Taha Alselwi, Serap Çakar Kaman, Beyza Eken   +2 more
wiley   +1 more source

Knowledge extraction and retrieval-augmented generation for intelligent maintenance of wind power equipment based on graph attention networks

Chinese Journal of Mechanical Engineering
The adoption of deep learning in intelligent operation and maintenance of wind turbines has improved fault detection and classification accuracy. However, most existing studies focus primarily on the fault identification stage, while the crucial task of ...
Xueyi Li, Gang Li, Tianyang Wang, Zhilin Dong, Zhaoye Qin, Fulei Chu   +5 more
doaj   +1 more source

GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs

AIChE Journal, Volume 72, Issue 10, October 2026.
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin, Artur M. Schweidtmann   +1 more
wiley   +1 more source

SG-RAG MOT: SubGraph Retrieval Augmented Generation with Merging and Ordering Triplets for Knowledge Graph Multi-Hop Question Answering

Machine Learning and Knowledge Extraction
Large language models (LLMs) often tend to hallucinate, especially in domain-specific tasks and tasks that require reasoning. Previously, we introduced SubGraph Retrieval Augmented Generation (SG-RAG) as a novel Graph RAG method for multi-hop question ...
Ahmmad O. M. Saleh, Gokhan Tur, Yucel Saygin   +2 more
doaj   +1 more source

From Idea to Implementation: Evaluating the Influence of Large Language Models in Software Development—An Opinion Paper

Applied AI Letters, Volume 7, Issue 3, October 2026.
Professionals' insights on the use of large language models (LLMs) in software development. This abstract highlights how transformer‐based models enhance productivity, reduce coding time, and assist with tasks such as code generation, debugging, and documentation, while also emphasizing potential challenges including overdependence and ethical ...
Sargam Yadav, Asifa Mehmood Qureshi, Abhishek Kaushik, Shubham Sharma, Roisin Loughran, Subramaniam Kazhuparambil, Andrew Shaw, Mohammed Sabry, Niamh St John Lynch, Nikhil Singh, Padraic O'Hara, Pranay Jaiswal, Roshan Chandru, David Lillis   +13 more
wiley   +1 more source

Hierarchical and Entity-Based Retrieval Augmented Generation

reservedRetrieval-Augmented Generation (RAG) has become a standard approach to address key challenges in large language models (LLMs), such as hallucinations and a lack of domain-specific knowledge.
SANDRINELLI, FEDERICO
core  

Incremental refinement of relevance rankings: Balancing relevance depth and scope

Journal of the Association for Information Science and Technology, Volume 77, Issue 10, Page 1247-1270, October 2026.
Abstract Delivering both relevant and topically diverse results is a key challenge in information retrieval (IR). This study introduces a hybrid method that incrementally refines rankings by combining probabilistic topic modeling (latent dirichlet allocation [LDA]) with citation‐based pennant retrieval grounded in Relevance Theory (RT), optimizing for ...
Müge Akbulut, Yaşar Tonta
wiley   +1 more source

Toward a Smart Learning Health System: An Ontology‐Based Framework

Learning Health Systems, Volume 10, Issue 4, October 2026.
ABSTRACT Background Learning health system (LHS) frameworks have been presented in multiple forms, but there is no standardized representation that captures both their core concepts and the relationships among them. This limits their practical use by health services seeking to design, implement, and evaluate LHS capabilities in changing sociotechnical ...
Meg Ma, Ping Yu, Louise D. Hickman
wiley   +1 more source

Evaluating base and retrieval augmented LLMs with document or online support for evidence based neurology

npj Digital Medicine
Effectively managing evidence-based information is increasingly challenging. This study tested large language models (LLMs), including document- and online-enabled retrieval-augmented generation (RAG) systems, using 13 recent neurology guidelines across ...
Lars Masanneck, Sven G. Meuth, Marc Pawlitzki   +2 more
doaj   +1 more source