RAG Text Chunking Strategies: Optimize LLM Knowledge Access
Author(s): Abinaya Subramaniam Originally published on Towards AI. If retrieval is the search engine of your RAG system, chunking is the foundation the search engine stands on. Even the strongest LLM fails when the chunks are too long, too short, noisy, or cut at the wrong place. That is why practitioners often say: “Chunking determines 70% of RAG quality.” Good chunking helps the retriever find information that is complete, contextual, and relevant while bad chunking creates fragmented, out […]