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Parameter-Efficient Fine-Tuning: LoRA, QLoRA, and DoRA

Year: 2026

Type: article

Abstract: A technical note comparing parameter-efficient fine-tuning techniques for large language models, including Low-Rank Adaptation (LoRA), its quantized variant QLoRA, and Weight-Decomposed Low-Rank Adaptation (DoRA).

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.21610032

Author: Santos, Dheiver

Language: English

Topic: Domain Adaptation and Few-Shot Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7171290821

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