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Apr 17, 2026 · Artificial Intelligence

Bridging the Semantic Gap in RAG: Solving Mismatched Queries and Vector Store Answers

The article explains why RAG systems often retrieve irrelevant results due to a semantic gap between colloquial user questions and formal document language, and presents a four‑layer solution—including query rewriting, HyDE, multi‑query expansion, hierarchical indexing, hybrid search with RRF, rerankers, and embedding fine‑tuning—to systematically close that gap.