LeWM is a ~15M-parameter JEPA world model that trains end-to-end from pixels with only next-embedding prediction plus a Gaussian latent regularizer, cutting loss hyperparameters to one.
Springer Science & Business Media
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LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
LeWM is a ~15M-parameter JEPA world model that trains end-to-end from pixels with only next-embedding prediction plus a Gaussian latent regularizer, cutting loss hyperparameters to one.