Back to AI Lab
Geometry
Research papers, repositories, and articles about geometry
Showing 2 of 2 items
GeoDM: Geometry-aware Distribution Matching for Dataset Distillation
Proposes GeoDM, a dataset distillation framework that performs distribution matching in a product space of Euclidean, hyperbolic, and spherical manifolds, with learnable curvature and weights. This geometry-aware approach yields lower generalization error bounds and consistently outperforms prior distillation methods by better aligning synthetic and real-data manifolds. ([arxiv.org](https://arxiv.org/abs/2512.08317?utm_source=openai))
Xuhui Li, Zhengquan Luo
Do Foundation Models Know Geometry? Probing Frozen Features for Continuous Physical Measurement
Probes frozen vision backbones for tasks like measuring lengths and angles. Tests how much real-world geometry is already baked into general-purpose models.
Yakov Pyotr Shkolnikov