Sign inGet started
Paper · arXiv

Mental Model Management: An Operator-Based Framework for LLM Memory

Large language models process large amounts of information but usually lack an explicit mechanism for maintaining compact and evolving conceptual representations. We introduce Mental Model Management (3M), a framework in which knowledge is represented as mental models consisting of compact chunks. Rather than accumulating text passages, 3M continuously integrates new information into an existing conceptual representation. A set of operators extracts knowledge, retrieves relevant models, adds and updates chunks, reorganizes representations, detects inconsistencies, and derives new knowledge. We describe the main 3M operators and illustrate each operation using Evolution Strategies as a run...

AuthorsOliver Kramer
Primary categorycs.AI
Published16 August 2026
Last updated at source16 August 2026
cs.AIcs.NE
Embed this entry
<iframe src="https://silytics.si/embed/item/90330d83-a391-4500-a70a-a805d8acc413" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.