A knowledge graph is a technology for organizing and representing knowledge in a graph structure, which builds a computable and inferable knowledge base by abstracting entities, attributes, and relationships. The graphical data structure allows machines to process and understand complex information more naturally, making data retrieval and analysis more efficient. In recent years, knowledge graphs … Read more
The RAG (Retrieval-Augmented Generation) model, commonly referred to as the RAG system, is widely used in large model applications. The principle of the model is quite simple: it retrieves information from a dataset based on user needs and then uses a large model for reasoning and generation. The advantage of RAG lies in its ability … Read more
Introduction Recently, while reviewing the papers I had previously studied in depth, I found that some notes were still very valuable. I made some minor adjustments and am publishing them for everyone to see. LLama3 is a paper from a few months ago, but each reading still brings new insights. This article discusses key points, … Read more
Figure: Agentic RAG (Image from the author) 1. Introduction Given the way technology evolves, we have become accustomed to thinking about certain solution constructs from the perspective of specific tools and platforms. For example, Retrieval-Augmented Generation (RAG) is ubiquitous in today’s Gen AI world. Given its emergence in the Gen AI era, we mainly view … Read more