---
id: 20260624-T0-10
title: "AlphaMemo：用于金融Alpha挖掘的结构化记忆机制"
title_en: "AlphaMemo: Structured Memory for Alpha Mining Agents"
url: https://ai.daily.yangsir.net/daily/20260624-T0-10
issue_date: 2026-06-24
publish_date: 2026-06-23T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2606.20625
---

# AlphaMemo：用于金融Alpha挖掘的结构化记忆机制

针对 LLM 智能体在金融 Alpha 挖掘中面临的组合搜索空间大和反馈噪声高的问题，研究人员提出了 AlphaMemo。该框架包含一个结构化的搜索-处理记忆模块，能够存储和检索有效的因子发现路径。实验表明，该方法能显著减少冗余发现并提升挖掘效率。

## English Version

**AlphaMemo: Structured Memory for Alpha Mining Agents**

To address challenges in financial alpha mining such as vast combinatorial search spaces and noisy feedback, researchers propose AlphaMemo. This framework features a structured search-process memory that stores and retrieves effective factor discovery paths, significantly reducing redundancy and improving mining efficiency.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2606.20625)

**详情页**：https://ai.daily.yangsir.net/daily/20260624-T0-10

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