LatentVerse: A Framework for Understanding Shared and Modality-Specific Information in Multimodal Latent Representations
Latent embeddings have become a central data abstraction in modern machine learning, especially in biomedicine, where foundation models are increasingly used to encode multimodal data like clinical text, medical images, omics, and physiological signals. However, the utility and value of these representations depends on...