Introduction to RAG Technology: A New Journey in Large Model Application Development

Introduction to RAG Technology: A New Journey in Large Model Application Development

What is RAG Technology RAG, or Retrieval-Augmented Generation technology, is an AI architecture that combines retrieval and generation. It enhances the output quality of language models by retrieving external knowledge. This is akin to equipping large language models with an intelligent knowledge base, enabling them to retrieve and reference relevant information in real-time while generating … Read more

RAG-Check: A Novel AI Framework for Multimodal Retrieval-Augmented Generation

RAG-Check: A Novel AI Framework for Multimodal Retrieval-Augmented Generation

Large Language Models (LLMs) have made significant progress in the field of generative artificial intelligence, but they face the “hallucination” problem, which is the tendency to generate inaccurate or irrelevant information. This issue is particularly severe in high-risk applications such as medical assessments and insurance claims processing. To address this challenge, researchers from the University … Read more

Principles and Practical Applications of RAG Retrieval-Augmented Generation

Principles and Practical Applications of RAG Retrieval-Augmented Generation

RAG 75% for retrieval, 25% for generation. All aimed at enhancing the ability to retrieve relevant contextual information. 1. RAG Working Principle and Technical Architecture RAG (Retrieval-Augmented Generation) is a technical architecture that combines information retrieval and generation models. Its basic working principle is to enhance the output of the generation model through the retrieval … Read more

Unlocking Efficient Data Retrieval with Query Construction Techniques in RAG Systems

Unlocking Efficient Data Retrieval with Query Construction Techniques in RAG Systems

Click 👇🏻 to follow, article from “ With the expanding application of large language models (LLMs), Retrieval-Augmented Generation (RAG) has become a mature technology. The popularity of products like txt2sql and ChatBI highlights the increasing importance of query construction techniques. This article analyzes the process of query construction and illustrates, through examples, how to transform … Read more

Mastering RAG Series 2: Query Translation Techniques

Mastering RAG Series 2: Query Translation Techniques

LLM (Large Language Model) is a powerful new platform, but they are not always trained on data that is relevant to our tasks or the most recent data. RAG (Retrieval Augmented Generation) is a general method that connects LLMs with external data sources (such as private data or the latest data). It allows LLMs to … Read more

Overview of 15 Classic RAG Frameworks (Part 2)

Overview of 15 Classic RAG Frameworks (Part 2)

Source: Deep Learning and Large Models (LLM) This article is approximately 3500 words long and is recommended for a 9-minute read. This article delves into the development of Retrieval-Augmented Generation (RAG), from basic concepts to the latest technologies. 4. Overview of Existing RAG Frameworks Agent-Based RAG A new agent-based Retrieval-Augmented Generation (RAG) framework adopts a … Read more

Mastering RAG: The Basics of Retrieval-Augmented Generation

Mastering RAG: The Basics of Retrieval-Augmented Generation

LLM (Large Language Model) is a powerful new platform, but they are not always trained on data relevant to our tasks or the latest data. RAG (Retrieval Augmented Generation) is a general method that connects LLMs with external data sources (such as private or up-to-date data). It allows LLMs to use external data to generate … Read more

RAG vs Fine-Tuning: A Guide for Domain-Specific AI Models

RAG vs Fine-Tuning: A Guide for Domain-Specific AI Models

Machine Heart Report Editor: Rome Retrieval-Augmented Generation (RAG) and Fine-tuning are two common methods to enhance the performance of large language models. So, which method is better? Which is more efficient when building applications in specific domains? This paper from Microsoft serves as a reference for your choice. When constructing large language model applications, there … Read more

Query Optimization Techniques in RAG

Query Optimization Techniques in RAG

A Survey of Query Optimization in Large Language Models Paper Link:https://arxiv.org/pdf/2412.17558 Published by: Tencent Large Language Models (LLMs) are becoming increasingly popular, but they also face challenges such as “hallucination” when dealing with domain-specific tasks or those requiring specialized knowledge. Retrieval-Augmented Generation (RAG) technology has emerged as a key method for enhancing model performance, with … Read more