Author

Tolga Birdal

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#machine learning Preprint Sep 2026

Task-Induced Riemannian Metrics for Vision Transformer Feature Spaces

Methods operating on Vision Transformer (ViT) feature spaces typically rely on Euclidean distance or cosine similarity. This assumes that every direction is equally meaningful, but there is no reason to believe the true task geometry has this property. The task-sensitive geometry of the feature space is given by the pu...

Andrew Bond, Ege Erdem Ozlu, Tuna Çimen et al. · 0 citations

Jul 2026

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models

Geometric foundation models, such as the Visual Geometry Grounded Transformer (VGGT), provide strong 3D priors from unposed images. However, such models operate purely in a feed-forward, deterministic regime, \ie~they cannot generate plausible geometry beyond what the input views directly support. Generative models for...

Lisa Weijler, Irene Ballester, Guofeng Mei et al. · arXiv.org · 0 citations