Semantic Chunking for RAG: Optimizing Retrieval-Augmented Generation
Semantic Chunking is a context-aware text splitting technique that groups sentences by meaning rather than splitting by fixed sizes. This preserves semantic relationships and dramatically improves retrieval accuracy in RAG systems by ensuring each chunk contains complete, related ideas. If you’ve built a RAG system, you’ve probably noticed something frustrating. Sometimes your AI gives you […]
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