---
id: 20260324-T0-12
title: "HyEvo：自进化混合代理工作流提升推理效率"
title_en: "HyEvo: Self-evolving hybrid workflows boost reasoning efficiency"
url: https://ai.daily.yangsir.net/daily/20260324-T0-12
issue_date: 2026-03-24
publish_date: 2026-03-23T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2603.19639
---

# HyEvo：自进化混合代理工作流提升推理效率

斯坦福大学团队提出HyEvo，一种可自动进化的混合代理工作流系统。该系统结合多种模型能力，通过迭代优化任务执行路径，在复杂推理任务上比单一LLM方法提升30%效率。研究显示，混合架构能更好地处理多步骤任务，减少错误并降低计算成本。

## English Version

**HyEvo: Self-evolving hybrid workflows boost reasoning efficiency**

Stanford researchers developed HyEvo, a self-evolving hybrid agentic workflow system that combines multiple model capabilities. By iteratively optimizing task execution paths, it achieves 30% higher efficiency than single LLM methods on complex reasoning tasks. The hybrid architecture demonstrates superior performance on multi-step tasks, reducing errors and computational costs.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2603.19639)

**详情页**：https://ai.daily.yangsir.net/daily/20260324-T0-12

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