AI RESEARCH
hZACH-ViT: Curved Latent Geometry for Compact Vision Transformers in Low-Data Medical Imaging
arXiv CS.CV
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ArXi:2606.00906v1 Announce Type: new Compact Vision Transformers are attractive for medical imaging in low-data and resource-constrained settings, but most existing variants assume that Euclidean latent geometry is sufficient for organizing image representations. We We evaluate Poincar\'e, Klein, and spherical hZACH-ViT heads on seven MedMNIST datasets under an identical few-shot protocol with 50 samples per class and five random seeds. The completed benchmark contains 770