SAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
cs.AI
Submitted: 2026-05-12
Updated: 2026-09-22
Code: https://github.com/memodb-io/memobase.https:
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Annotation-Free Reinforcement Learning Query Rewriting via Verifiable Search Reward
- HaluMem: Evaluating Hallucinations in Memory Systems of Agents
- Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
- Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
- From Local to Global: A Graph RAG Approach to Query-Focused Summarization
- LightRAG: Simple and Fast Retrieval-Augmented Generation
- AmazonQA: A Review-Based Question Answering Task
- From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
- Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions
- LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning
- GPT-4o System Card
- Unsupervised Dense Information Retrieval with Contrastive Learning
- TiMem: Temporal-Hierarchical Memory Consolidation for Long-Horizon Conversational Agents
- Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation
- Locomo-Plus: Beyond-Factual Cognitive Memory Evaluation Framework for LLM Agents
- MemOS: An Operating System for Memory-Augmented Generation (MAG) in Large Language Models
- GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation
- Zep: A Temporal Knowledge Graph Architecture for Agent Memory
- AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction
- MIRIX: Multi-Agent Memory System for LLM-Based Agents
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
- VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection