4 accepted papers
Multimodal alignment fails under deployment shift because standard objectives entangle cross-modal dependence with marginal-sensitive geometry. Stable Spectral Copula Alignment (SSCA) provides a deployment protocol targeting copula-stable dependence under strictly monotone marginal distortions, with…
This paper presents an optimized approach to enhance the computation of Hirschfeld-Gebelein-Rényi (HGR) maximal correlation, addressing computational and efficiency challenges in large-scale neural networks and multimodal learning. The UniFast HGR framework introduces three key innovations: replacin…
Hyperspectral imaging offers extensive spectral and spatial information. However, effectively utilizing this data for accurate classification remains a challenge. This study introduced the CASSX-Net, a novel framework designed to capture both short- and long-range dependencies in HSI data for land c…
Significant progress has been achieved using Vision Transformers (ViTs) in computer vision. However, challenges persist in modeling multi-scale spatial relationships, hindering effective integration of fine-grained local details and long-range global dependencies. To address this limitation, a Multi…