Exploring parameter-efficient fine-tuning (PEFT) of billion-parameter vision models with QLoRA and DoRA: insights into generalization for limited-data image classification under a 98:1 test-to-train regime

Fuente: arXiv

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Bibliographic Details
Main Authors:	Yang, Haiyu, Sharma, Sumit, Liu, Enhong, Hostens, Miel
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2603.17782