Rerank the Regime, Not the Corpus
TL;DR for operators A RAG system can fail even when retrieval looks superficially healthy: several top-ranked documents repeat the query vocabulary, while the document that actually contains the answer sits lower in the list. The paper studies a reranking rule designed specifically for that situation.1 Instead of rewarding more query-document overlap, it removes words that exactly or semantically echo the query and scores what remains. In an eight-theme controlled keyword-stuffing diagnostic, this semantic variant improves mean target rank from 2.88 to 1.25 and pushes stuffed distractors from mean rank 2.00 to 4.50. ...