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AI & Machine Learning · Intermediate

Chunking

Splitting documents into smaller passages before embedding them for retrieval.

Definition

Chunk size and boundaries strongly affect RAG quality: chunks too small lose context, chunks too large dilute relevance and waste tokens. Strategies include fixed-size with overlap, sentence or paragraph-based, hierarchical and semantic chunking.

Example

Splitting manuals into 500-token chunks with 50-token overlap.

Exam tip

If answers lack context, increase chunk size or overlap; if retrieval is noisy, reduce chunk size.

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