agent/papers/items/2026-2606-00610-memgraphrag-memory-based-multi-agent-system-for-graph-retrieval-augmented-genera.md

Paper: MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation

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type: paper title: "MemGraphRAG: Memory-based Multi-Agent System for Graph Retrieval-Augmented Generation" authors: Chuanjie Wu, Zhishang Xiang, Yunbo Tang, Zerui Chen, Qinggang Zhang, Jinsong Su year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.00610 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-30 updated_at: 2026-05-30 status: queued relevance: high topics:

• agent-evaluation
• memory
• multi-agent
• rag
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.IR
• cs.AI
• cs.MA related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 20 collection_queries: rag-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: rag-agent
• inferred topics: agent-evaluation, memory, multi-agent, rag, reasoning, tool-use
• arXiv categories: cs.IR, cs.AI, cs.MA
• collection score: 20

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.00610