Maximal Marginal Relevance for RAG
Top-k vector search keeps returning near-duplicate chunks that fill the context window. How Maximal Marginal Relevance reranks for relevant, diverse results.
#Retrieval(4)
Parent Document Retrieval: Search Small, Answer Big
Small chunks search precisely but read like fragments. Parent document retrieval matches on child chunks, then feeds the whole parent to the model.
HyDE: Hypothetical Document Embeddings for RAG
Vector search fails when a short question looks nothing like its answer. HyDE has an LLM draft a fake answer, embeds that, and retrieves against it instead.
Contextual Retrieval for RAG Pipelines
Chunking a document for RAG strips each piece of its context. Contextual retrieval adds an LLM-written note to every chunk before you index it.