In the news
Copy the Same, Distill the Difference: Initializing Linear Vision Transformers
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- Researchers show how to initialize linear Vision Transformers by copying MLP weights from Softmax ViTs and distilling attention behavior rather than copying attention weights directly.
- Why it matters
- Matters for engineers optimizing vision models who want faster inference by switching from standard to linear attention without full retraining.
- Watch out
- Method tested on various linear ViT variants and datasets, but real-world deployment performance across different domains remains to be validated.
- distill
- attention
- token
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