AIWalker

Feb 26, 2026 · Artificial Intelligence

Overcoming Vision Transformer Bottlenecks: The Plug‑and‑Play Upgrade of ViT‑5

ViT‑5 systematically revisits five years of Transformer architecture advances, introducing seven plug‑and‑play components—LayerScale, RMSNorm, GeLU, dual positional encodings, high‑frequency RoPE for register tokens, QK‑Norm, and bias‑free projections—that together raise ImageNet‑1k Top‑1 accuracy to 84.2% (Base) and achieve superior performance across classification, generation, and segmentation tasks.