LoRA: Low-Rank Adaptation of Large Language Models
Summary
LoRA: Low-Rank Adaptation of Large Language Models (2021) introduced the standard parameter-efficient way to adapt a large model without training all of its weights. You freeze the base model and learn a pair of low-rank update matrices, which makes fine-tuning cheaper to store and often cheaper to run.
What it introduced: low-rank adaptation (LoRA) of attention (and later other) weights, with experiments showing that these small updates can match full fine-tuning on many tasks.
What it led to: QLoRA and the adapter ecosystem now used to fine-tune open chat models on modest hardware. Live notes: 2305-14314-qlora and hf-transformers-quantization-overview.
If you are adapting a large open model on one GPU, this is the method most later adapter recipes start from. Where to read it: https://arxiv.org/abs/2106.09685 (v2, last revised 16 Oct 2021).
The paper is posted on arXiv under the arXiv non-exclusive distribution license. This note links to it rather than reproducing it. The note itself is CC BY 4.0.
License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Pointer by iinventedlight (AI-assisted). Paper license: arXiv non-exclusive distribution; this note links to it and does not reproduce it.
License: CC-BY-4.0 · Pointer by iinventedlight (AI-assisted). Source: Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, LoRA: Low-Rank Adaptation of Large Language Models (arXiv non-exclusive distribution license). This note links to the paper rather than reproducing it.
Cite this
'iinventedlight (AI-assisted)'. 2026. "LoRA: Low-Rank Adaptation of Large Language Models." iinventedlight Library, iil:note:5h8rpndd, version of 2026-11-11. https://iinventedlight.com/library/notes/2106-09685-lora/. License: CC-BY-4.0.
@misc{iil_note_5h8rpndd,
author = {{'iinventedlight (AI-assisted)'}},
title = {{LoRA: Low-Rank Adaptation of Large Language Models}},
howpublished = {iinventedlight Library},
year = {2026},
date = {2026-11-11},
url = {https://iinventedlight.com/library/notes/2106-09685-lora/},
note = {Permanent ID iil:note:5h8rpndd. License: CC-BY-4.0.},
}Spotted a mistake? Use the MCP feedback tool or email hello@iinventedlight.com.
For language models and agents: start at /llms.txt | /agents.md | /.well-known/agent-library.json. This page in Markdown: /library/notes/2106-09685-lora.md.