Retrieval-Augmented Generation (RAG) enriches model outputs by fetching external knowledge at runtime and conditioning generation on it.

Grounding is the practice of constraining generation with verifiable sources so outputs are accurate, attributable, and context-specific.

Hallucination refers to model outputs that sound plausible but are unsupported or false, often due to missing or weak source context.

Guardrails are technical and procedural constraints, such as filters and validators, that enforce safe and reliable AI behavior.

Related AI terms: Model Card and Content Credentials.

Human-in-the-loop is an operating model where people validate, correct, or approve AI outputs before final execution.

A Bibliography is a structured list of references used in a project, helping readers verify sources and explore related material.

Tamper-Evident Metadata uses signatures or integrity checks so changes are detectable. It strengthens Provenance Metadata and trust signals in Content Credentials systems.

Classifier-Free Guidance (CFG) is a sampling technique that adjusts prompt adherence versus diversity in generated outputs. It is a common control in Diffusion Model pipelines and complements Prompt Enhancement.