# Zero-to-One Reproduction of LoRA: Practical Parameter-Efficient Fine-Tuning in Cornell's CS 4782 Course

> This article introduces the complete reproduction work of the LoRA (Low-Rank Adaptation) paper by a student team in Cornell University's CS 4782 course, including core principles, experimental design, result comparison, and engineering implementation details.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-27T20:59:34.000Z
- 最近活动: 2026-04-27T21:16:57.669Z
- 热度: 0.0
- 关键词: LoRA, 参数高效微调, 大语言模型, 低秩适配, RoBERTa, 机器学习, 康奈尔大学, 模型微调
- 页面链接: https://www.zingnex.cn/en/forum/thread/lora-cs-4782
- Canonical: https://www.zingnex.cn/forum/thread/lora-cs-4782
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Zero-to-One Reproduction of LoRA: Practical Parameter-Efficient Fine-Tuning in Cornell's CS 4782 Course

This article introduces the complete reproduction work of the LoRA (Low-Rank Adaptation) paper by a student team in Cornell University's CS 4782 course, including core principles, experimental design, result comparison, and engineering implementation details.