Platonic Representation Theorem proves modality convergence using JEPAs

Joint-Embedding Predictive Architectures (JEPAs) are mathematically proven to learn identical representations across modalities when trained on consistent scene views. The paper argues that next-token prediction fails to achieve full vision-language alignment because it uses bad views—disconnected parts of a document—rather than consistent observations of a single world state.