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Grounding is connecting an AI model's outputs to verifiable external sources or data so the responses can be traced and trusted.
Grounding, connecting an AI model's outputs to verifiable external sources or data so the responses can be traced and trusted.
Grounding is a primary defence against fabrication: rather than answering from its parameters alone, a grounded system draws on retrieved documents or authoritative data and can cite them. Retrieval-augmented generation is a common grounding technique. Grounding reduces, but does not eliminate, hallucination, the model can still misuse the sources it retrieves.
Source: Machine-learning practice
Grounding is a primary defence against fabrication: rather than answering from its parameters alone, a grounded system draws on retrieved documents or authoritative data and can cite them. Retrieval-augmented generation is a common grounding technique. Grounding reduces, but does not eliminate, hallucination, the model can still misuse the sources it retrieves.
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