SmartFAQs.ai
Back to Learn
Intermediate

Confabulation

The generation of statistically plausible but factually unsupported output by an LLM; while mitigating it via RAG improves accuracy, it introduces trade-offs in system latency and the risk of 'refusal to answer' if retrieval fails.

Definition

The generation of statistically plausible but factually unsupported output by an LLM; while mitigating it via RAG improves accuracy, it introduces trade-offs in system latency and the risk of 'refusal to answer' if retrieval fails.

Disambiguation

Distinguishes 'filling in the blanks' with false logic from simple retrieval failures or software bugs.

Visual Metaphor

"A confident tour guide inventing historical dates for a monument to avoid admitting they don't know the answer."

Key Tools
RagasTruLensLangSmithDeepEvalArize Phoenix
Related Connections

Conceptual Overview

The generation of statistically plausible but factually unsupported output by an LLM; while mitigating it via RAG improves accuracy, it introduces trade-offs in system latency and the risk of 'refusal to answer' if retrieval fails.

Disambiguation

Distinguishes 'filling in the blanks' with false logic from simple retrieval failures or software bugs.

Visual Analog

A confident tour guide inventing historical dates for a monument to avoid admitting they don't know the answer.

Related Articles