---
id: 20260604-T0-04
title: "ReLoRA：大模型服务快速部署的知识重用方案"
title_en: "ReLoRA: Knowledge-Reusing Adaptation for LLM Services"
url: https://ai.daily.yangsir.net/daily/20260604-T0-04
issue_date: 2026-06-04
publish_date: 2026-06-03T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2606.02606
---

# ReLoRA：大模型服务快速部署的知识重用方案

arXiv论文提出ReLoRA方案，解决大模型持续更新导致LoRA适配器失效的问题。该方法支持服务提供商在基础模型频繁更新的情况下，快速部署演化的LLM服务，保持任务特定性能。研究显示ReLoRA能显著减少模型适应时间。

## English Version

**ReLoRA: Knowledge-Reusing Adaptation for LLM Services**

An arXiv paper proposes ReLoRA, a solution to the problem of LoRA adapters becoming invalid when base models update frequently. The method allows service providers to rapidly deploy evolving LLM services while maintaining task-specific performance, significantly reducing model adaptation time.

---

**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2606.02606)

**详情页**：https://ai.daily.yangsir.net/daily/20260604-T0-04

---

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