SOURCE-LINKED INTELLIGENCE
Hub-Spectral Activation of Latent Multimodal Knowledge
Multimodal representation learning seeks shared representations for cross-modal retrieval and knowledge transfer. Hub-based binding reduces pairwise supervision costs, but separate hub connections cannot guarantee reliable alignment between modalities without direct joint training. We introduce Hub-Spectral Activation (HSA), a closed-form method for recovering and activating the hub-readable component of latent multimodal knowledge in frozen representations. We formalize this knowledge as source-induced cross-modal dependence and characterize the component determined by the second-order statis
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T12:27:42.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.