Papers With Code
metadata only
Jev-Mem: System-One-Controlled Agentic Memory for Efficient AI Agents
Agentic memory is becoming essential for long-horizon AI agents, yet many existing systems rely on autoregressive LLMs to control how memories are organized, retrieved, and used, placing expensive generation on the critical path of memory operations. We introduce \method, a new agentic memory archit
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Jev-Mem: System-One-Controlled Agentic Memory for Efficient AI Agents#1050175
- CONTINUITY WITHOUT MEMORY Multi-Platform Linked Public Building and the Architecture of Stateless AI Work#696603
- A Practical Playbook for Using AI Link Building Software Without Losing SEO Control#434987
- MemoNoveltyAgent: A Historical Research Memory-Aware Agent Workflow for Paper Novelty Assessment#793606
- MemoNoveltyAgent: A Historical Research Memory-Aware Agent Workflow for Paper Novelty Assessment#789602
Record · ID 1054723
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive