---
language: en
title: "Non-parametric memory"
description: "Non-parametric memory is information kept outside a model’s parameters and accessed through retrieval, such as a document index queried in RAG."
canonical: "https://tropk.ai/en/resources/glossary/non-parametric-memory"
last_modified: "2026-10-12T16:13:34.451Z"
---

# Non-parametric memory

Reviewed on 2026-10-06.

## What it means

Non-[parametric memory](/en/resources/glossary/parametric-memory) is information stored outside a model’s learned parameters and made available through [retrieval](/en/resources/glossary/information-retrieval) mechanisms. In the paper that introduced [RAG](/en/resources/glossary/rag), it corresponds to a vector index of Wikipedia passages. The system selects documents from this index to support generation, combining an inspectable external source with the knowledge already represented in the model.

## Why it matters for marketing

For marketing, this separation makes it possible to investigate whether an outdated answer came from the source being queried. Correcting a document and updating its representation in the index can make the current version retrievable without retraining the generator. This depends on the integration: publishing on the website does not prove that the external source incorporated the change or that the document will be selected.

## Example in practice

Imagine an internal assistant that explains a store’s returns policy. The official page says fifteen days, but the passage retrieved from the index still says sixty days. After noticing the discrepancy, the team updates the non-parametric memory and tests retrieval again. The change is made to the document version, leaving the model used for generation unchanged.

## How to apply or verify

Ask the person responsible for the integration for the retrieved documents or passages, their source, and the date the source was updated. Check whether the current version was processed and selected for the question. Compare the retrieved information with the answer: even an accurate source can be interpreted incorrectly. Record ingestion, selection, and evidence-use failures separately.

## Important distinctions

The term does not mean the entire system is free of parameters: the retriever may use trained models to locate documents. The distinction describes where the retrievable knowledge is stored. Non-parametric memory also does not guarantee live internet search; an external index may be static, private, or outdated, depending on the choices made in the integration.

## Sources and references

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](<https://arxiv.org/html/2005.11401v4>) — Patrick Lewis e coautores / arXiv

## Continue a leitura

- [Parametric memory](</en/resources/glossary/parametric-memory>)
- [RAG](</en/resources/glossary/rag>)
- [Information retrieval](</en/resources/glossary/information-retrieval>)

## About the author

[Vinicius Pacheco](</en/team/vinicius-pacheco>)

Responsible for Tropk’s technical content, focusing on crawling, indexing, structured data, and agent access to content.

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