Retrieval-Augmented Generation: A Comprehensive Survey of Architectures, Enhancements ...
This section presents a comparative analysis of Retrieval-Augmented Generation (RAG) frameworks in short-form question answering, emphasizing their relative improvements over raw large language model (LLM) baselines and retrieval-augmented baselines.

Engineering RAG Systems for Real-World Applications: Design, Development, and ...
Retrieval-Augmented Generation (RAG) systems are emerging as a key approach for grounding Large Language Models (LLMs) in external knowledge, addressing limitations in factual accuracy and contextual relevance.

Intelligent Question Answering System for Power Regulations based on RAG - IEEE Xplore
To address the issues posed by the complexity and vast amount of regulations in the power industry, this paper proposes an intelligent question answering system based on the Retrieval-Augmented Generation (RAG) model.

Advancing engineering research through context-aware and knowledge graph ... - Frontiers
This study introduces a collection of new and highly deployable RAG-LLMs built on the n8n automation system and specifically designed for engineering domains.

Retrieval-Augmented Generation Approach: Document Question Answering using Large ...
This study introduces the Retrieval Augmented Generation (RAG) method to improve Question-Answering (QA) systems by addressing document processing in Natural Language Processing problems.

Research on the construction and application of retrieval enhanced generation (RAG ...
Generative pre-trained language models have demonstrated strong capabilities in natural language processing tasks, but they still suffer from “fact hallucination” and weak knowledge...

Searching for Best Practices in Retrieval-Augmented Generation
Here, we investigate existing RAG approaches and their potential combinations to identify optimal RAG practices. Through extensive experiments, we suggest several strategies for deploying RAG that balance both performance and efficiency.

A Systematic Literature Review of Retrieval-Augmented Generation: Techniques, Metrics ...
Background: Retrieval-augmented generation (RAG) aims to reduce hallucinations and outdated knowledge by grounding LLM outputs in retrieved evidence, but empirical results are scattered across tasks, systems, and metrics, limiting cumulative insight.

A Study on Question-answering Retrieval System Based on Large Language Models and RAG ...
The core section of this paper designs and implements a question-answering retrieval system based on large models and RAG technology, detailing its system architecture, workflow, and key implementation technologies using LangChain and vector databases.

      >> Live EBAY Auctions