ModelRefs / Semantic Memory — AI Glossary
Semantic Memory — AI Glossary
Memory of generalized facts and relationships extracted from prior interactions, stored in a knowledge graph or structured store.
Overview
Used to give agents domain knowledge that persists across episodes without re-stuffing the prompt each time. Contrast with episodic memory (event-level) and working memory (current context window).
Reference details
| Topic | agents |
|---|---|
| Last reviewed | 2026-06-24 |
Related terms
How it works
- Candidate facts are extracted from conversation or documents and written as standalone statements, since a fact that only makes sense in its original context cannot be retrieved usefully.
- Each is stored with provenance — when it was learned and from what — because the entry is a model's claim rather than a verified record.
- Retrieval is by relevance to the current turn, so only a few facts enter the prompt instead of the whole store.
- Contradictions are reconciled on write: a new fact that conflicts with an existing one must supersede it, or the store will return both and the model will pick arbitrarily.
- Entries are re-validated or expired, because a fact extracted once and never checked becomes stale silently and is retrieved with the same confidence.
Example: Why a contradiction is worse than a gap
An agent learns in March that a user's preferred region is EU, and in September that it is US. Stored without reconciliation, both entries match a region query and the model selects one — in practice often the better-embedded phrasing rather than the more recent fact. The user then sees a confident answer based on a six-month-old preference. An empty store would have prompted a question; the unreconciled one produced a wrong answer with no signal that anything was uncertain.
Commonly confused with
The counterpart to episodic memory: generalised facts rather than a record of events. It differs from a knowledge base in provenance — a knowledge base is authored and reviewed, whereas these facts were extracted by a model from conversation and inherit that model's errors. Treat entries as claims with a source, not as ground truth.
When to use it
Reach for it when:
- Durable facts about a user or domain should persist across sessions without being re-stated.
- Re-stuffing the same background into every prompt is wasting context.
- Facts are reusable across tasks rather than tied to one episode.
Reach for something else when:
- The information must be authoritative, where an authored and reviewed knowledge base belongs instead.
- The facts are episodic — what happened, and when — which is a different store.
- Nothing reconciles contradictions, in which case the store will eventually answer confidently and wrongly.
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Frequently asked questions
What is Semantic Memory?
Memory of generalized facts and relationships extracted from prior interactions, stored in a knowledge graph or structured store.
What concepts are related to Semantic Memory?
Closely related concepts include agentic memory, knowledge graph, memory.