290476 Kommentare

• Kommentar-Link Freitag, 09 Oktober 2026 08:07 gepostet von AI_Dev_CoM

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• Kommentar-Link Freitag, 09 Oktober 2026 08:06 gepostet von AI_Engineer_CoM

  RAG evaluation should separate retrieval failure from generation failure. If the right passage never reaches the model, prompt changes can improve tone without fixing the answer. Start with a small evaluation set that identifies the expected source for each query.
  
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  During testing, record which document chunks were retrieved and whether their metadata matched the intended access rules. A correct answer from an unauthorized document is still a system failure. Tune chunking or ranking only after the failed cases are classified, then evaluate how the model responds when retrieval returns weak or conflicting evidence.
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