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Daniel Pommer

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Jul 2026

On the Efficiency of LoRA Fine-Tuning for Vision-Language-Action Models in Industrial Robotic Manipulation

It is suggested that LoRA at r=32 with full vision encoder fine-tuning is a practical approach, reducing static peak VRAM from 36.2 to 10.8 GiB (parameters and optimizer states, activation memory excluded) without detectable performance loss.

Finn Ferchau, Daniel Pommer, Cristian Axenie · 0 citations

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