---
id: 20260512-T0-04
title: "GraphDC：大模型推理图算法能力提升50%"
title_en: "GraphDC Boosts LLM Graph Algorithm Reasoning by 50%"
url: https://ai.daily.yangsir.net/daily/20260512-T0-04
issue_date: 2026-05-12
publish_date: 2026-05-11T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2605.06671
---

# GraphDC：大模型推理图算法能力提升50%

GraphDC是一种分治多智能体系统，专门解决大模型在图算法推理中的性能瓶颈。该系统通过拓扑分解和分布式协作，将复杂图问题拆分为可处理的子任务，在标准数据集上推理速度提升50%。这一方法为AI在复杂网络分析、社交关系建模等场景提供了新工具，开发者可用其构建更高效的图计算应用。

## English Version

**GraphDC Boosts LLM Graph Algorithm Reasoning by 50%**

GraphDC is a divide-and-conquer multi-agent system addressing LLM limitations in graph algorithm reasoning. By decomposing complex graphs into manageable subtasks, it achieves 50% faster inference on standard datasets. This breakthrough enables developers to build more efficient graph applications for complex network analysis and social modeling.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2605.06671)

**详情页**：https://ai.daily.yangsir.net/daily/20260512-T0-04

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