---
id: 20260402-T0-12
title: "人脑终身记忆架构破解LLM遗忘症"
title_en: "Neuro-inspired memory architecture stops LLM forgetting"
url: https://ai.daily.yangsir.net/daily/20260402-T0-12
issue_date: 2026-04-02
publish_date: 2026-04-01T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2603.29023
---

# 人脑终身记忆架构破解LLM遗忘症

大模型缺乏持久结构化记忆，即使扩展上下文窗口，推理能力仍会下降85%。该研究基于神经科学设计终身记忆架构，支持长期交互和上下文敏感检索。实验显示，动态记忆管理使长期任务准确率提升40%，解决上下文窗口增长导致的推理衰减。

## English Version

**Neuro-inspired memory architecture stops LLM forgetting**

Lack of persistent memory causes LLMs to lose up to 85% reasoning accuracy as context windows expand. This neuroscience-grounded architecture enables lifelong interaction with dynamic memory management, boosting long-term task accuracy by 40% and solving context-induced degradation.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2603.29023)

**详情页**：https://ai.daily.yangsir.net/daily/20260402-T0-12

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*智语观潮 · Daily — https://ai.daily.yangsir.net/llms.txt*