The practice of anchoring AI outputs in verifiable external data sources (documents, databases, search results) to reduce hallucination and improve factual a...
Making sure the AI's answers are based on real facts, not just stuff it made up.
Connecting AI responses to real, verified information sources — like search results or documents — so answers are factual instead of invented.
The practice of anchoring AI outputs in verifiable external data sources (documents, databases, search results) to reduce hallucination and improve factual accuracy.
Conditioning model generation on retrieved evidence or structured knowledge to ensure outputs are faithful to source material — a key technique for reducing confabulation in production systems.
Establishing a causal information pathway from verified external sources to generated tokens, ensuring semantic faithfulness via retrieval conditioning, citation generation, and attribution verification — quantifiable through groundedness metrics and source-attribution F1.
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