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
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Freshness: 2026-04-02T02:30:40.136932+00:00Claims: 0
References: 0
Proof: partial
Distribution: unknown
PDF: https://arxiv.org/pdf/2603.17782v1
Repository: https://github.com/neis-lab/mmcows
First buyer signal: unknown
Distribution channel: unknown
Last proof check: 2026-03-19T21:58:08.308518+00:00
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