Retrieval-augmented generation - Open Access .click

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On Data Spaces for Retrieval Augmented Generation

Large Language Models (LLMs) have revolutionized knowledge retrieval from natural language queries. However, LLMs still face challenges regarding the creation of domain-specific and accurate answers. Recently, Retrieval Augmented Generation (RAG) architecture has been proposed as one approach to addressing these challenges.
Felix Hermsen +4 more
openaire +1 more source

Axioms for Retrieval-Augmented Generation

Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval (ICTIR)
Jan Heinrich Merker +4 more
openaire +1 more source

Improving large language model applications in biomedicine with retrieval-augmented generation: a systematic review, meta-analysis, and clinical development guidelines Open Access

Journal of the American Medical Informatics Association: JAMIA
Adam Wright, Allison McCoy
exaly

RadioRAG: Online Retrieval–Augmented Generation for Radiology Question Answering

Radiology: Artificial Intelligence
Lisa C. Adams, Christiane Kuhl, Keno Bressem +2 more
exaly

IRAGKR:Iterative retrieval augmented generation with fine-grained knowledge refinement

Neurocomputing
Lin Cao, Kangning Du
exaly

Retrieval augmented generation-driven information retrieval and question answering in construction management

Advanced Engineering Informatics
Chengke Wu, Longhui Liao
exaly

Effectiveness of retrieval augmented generation-based large language models for generating construction safety information

Automation in Construction
Seungjun Ahn, Hongjo Kim, Hoyoung Jeong
exaly

Retrieval augmented generation using engineering design knowledge

Knowledge-Based Systems
L Siddharth
exaly