arXiv stat.ML
· Papers
Multimodal Alignment Through Joint Kernel Entropic Gromov–Wasserstein Optimal Transport
arXiv:2608.04234v1 Announce Type: cross Abstract: We study the problem of aligning data from multiple modalities into a shared representation space, focusing on settings where strong pretrained unimodal encoders are available but cross-modal paired data are scarce. We propose a structure-preserving alignment framework,