We study the implicit bias of Riemannian gradient flow for hyperbolic multiclass classification with fixed class prototypes in hyperbolic space $\mathbb{H}^n$. Our framework accommodates general permutation invariant relative margin (PERM) losses, a class that includes cross entropy and other standard multiclass losses...
Xing-Run Li, Sho Kuno, Yusuke Mukuta et al.· 0 citations
The $\mathbb{SL}(n)$ space is introduced, a representation geometry defined by the simple $\det(A)=1$ constraint and a left invariant Schatten-$p$ Finsler structure that consistently outperforms a broad range of representation manifold baselines across graph benchmarks at different scales.
Xing-Run Li, Yusuke Mukuta, Xin Yang et al.· 0 citations
LF-MultiDiffusion is proposed, a training-free panorama generation method that extends MultiDiffusion to support linear projections between target and reference image spaces and achieves better visual quality, text alignment, and panoramic consistency than the strongest training-free baseline, while providing a 15.36%...