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6 RAG evaluation mistakes: retrieval, answers, and refusal
Build a layered RAG scorecard for evidence recall, context quality, groundedness, correctness, unanswerable questions, and over-refusal.
Oct 21, 2026 • Ranker.dev
Read moreRetrieval benchmarks: what BEIR and MTEB tell you
Use retrieval benchmarks to shortlist models, then check task, judgments, domain, contamination, and transfer with a local evaluation.
Oct 21, 2026 • Ranker.dev
Read moreHow to choose an embedding model: evaluate your own corpus
Compare embedding models on held-out local queries, relevance judgments, latency, index size, and migration cost rather than leaderboard rank.
Oct 21, 2026 • Ranker.dev
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