#llm
3 articles
Chronicle
3 posts2025
02- 02 May 21 Chunking Strategies in RAG Systems Retrieval-Augmented Generation (RAG) has become a key technology in the field of artificial intelligence, enhancing the output quality of large language models by incorporating external knowledge bases. In RAG systems, document chunking strategies are seemingly simple yet crucial components that directly impact retrieval accuracy and overall system efficiency. This article explores how various chunking strategies work, their advantages and disadvantages, and suitable application scenarios to help you choose the best solution for specific use cases.
- 03 Apr 11 What is RAG? RAG (Retrieval-Augmented Generation) is a technique that improves the accuracy of large language models and reduces hallucinations by incorporating user-specific data to enhance the quality and relevance of LLM responses.