Category:

Grounding Models

Category:

AI Reliability

Definition

Models designed to tie LLM outputs to real data sources.

Explanation

Grounding models reduce hallucinations by ensuring answers are supported by retrieved evidence, structured data, or factual databases. They operate as an intermediate layer between retrieval and LLM response generation. Grounding is essential in regulated or high-risk industries.

Technical Architecture

LLM → Grounding Engine → Evidence Retrieval → Verified Output

Core Component

Verifier, retriever, evidence scanner, contradiction detector

Use Cases

Legal AI, medical QA, enterprise copilots, analytics agents

Pitfalls

Grounding breaks when retrieval fails; costs increase

LLM Keywords

Grounded AI, Factual Grounding, Evidence-based LLM

Related Concepts

Related Frameworks

• RAG
• Verification Layers
• Fact Checking

• Grounded Response Pipeline

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