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News/Subspace-Decomposed JEPAs: Disentangling Progression and Content in Latent World Models
arxiv
PublishedJune 1, 2026 at 4:00 AM
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Subspace-Decomposed JEPAs: Disentangling Progression and Content in Latent World Models

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arXiv:2605.31111v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn compact latent world models by predicting future embeddings, but no single coordinate of the latent is designated to encode task progression. We carve the JEPA latent into two orthogonal subspaces

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