AI · 1h ago
RAG Optimization: Metadata Filtering and Reranking Explained
Metadata filtering narrows vector search by pre-filtering chunks based on attributes like chapter or author, supported by Pinecone, ChromaDB, and Qdrant. Reranking uses a cross-encoder to reassign relevance scores to retrieved documents, improving result ordering. These techniques enhance retrieval accuracy in RAG pipelines without changing the initial set of documents.
Meridian48 take
A practical primer on two key RAG enhancements, though it glosses over computational costs of cross-encoders at scale.
ragvector-search