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Completeness

Completeness refers to the degree to which an LLM-generated response addresses all components of a user's query using the entirety of the relevant retrieved context. In RAG architectures, it represents the ratio of identified ground-truth facts in the context that were successfully synthesized into the final output, often involving a trade-off between exhaustive detail and response latency.

Definition

Completeness refers to the degree to which an LLM-generated response addresses all components of a user's query using the entirety of the relevant retrieved context. In RAG architectures, it represents the ratio of identified ground-truth facts in the context that were successfully synthesized into the final output, often involving a trade-off between exhaustive detail and response latency.

Disambiguation

Distinguishes 'information coverage' from 'faithfulness' (hallucination-free) or 'relevance' (alignment with intent).

Visual Metaphor

"A Jigsaw Puzzle: Ensuring every relevant piece found in the box (retrieved context) is actually placed on the table to reveal the full picture for the user."

Conceptual Overview

Completeness refers to the degree to which an LLM-generated response addresses all components of a user's query using the entirety of the relevant retrieved context. In RAG architectures, it represents the ratio of identified ground-truth facts in the context that were successfully synthesized into the final output, often involving a trade-off between exhaustive detail and response latency.

Disambiguation

Distinguishes 'information coverage' from 'faithfulness' (hallucination-free) or 'relevance' (alignment with intent).

Visual Analog

A Jigsaw Puzzle: Ensuring every relevant piece found in the box (retrieved context) is actually placed on the table to reveal the full picture for the user.

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