---
id: 20260606-T0-05
title: "LANTERN：LLM长对话记忆层架构方案"
title_en: "LANTERN: Memory Layer for Long LLM Conversations"
url: https://ai.daily.yangsir.net/daily/20260606-T0-05
issue_date: 2026-06-06
publish_date: 2026-06-05T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2606.05182
---

# LANTERN：LLM长对话记忆层架构方案

arXiv发布LANTERN，解决大模型长对话遗忘问题。当对话历史压缩到有限上下文时，关键信息会被丢弃。LANTERN通过分层存档和时序记忆网络，主动保存长期信息，让模型在长对话中保持连贯性，提升复杂任务处理能力。

## English Version

**LANTERN: Memory Layer for Long LLM Conversations**

arXiv released LANTERN to solve long-context LLM memory loss. When conversation history is compressed to fit context windows, critical details are discarded. LANTERN uses layered archival and temporal retrieval to proactively save long-term information, maintaining coherence in extended conversations and improving complex task handling.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2606.05182)

**详情页**：https://ai.daily.yangsir.net/daily/20260606-T0-05

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