DiLA uses content-structure disentanglement driven by predictive bottlenecks to create semantically structured latent actions for high-fidelity video world models.
Pre-training con- textualized world models with in-the-wild videos for re- inforcement learning.Advances in Neural Information Processing Systems, 36:39719–39743, 2023a
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DiLA: Disentangled Latent Action World Models
DiLA uses content-structure disentanglement driven by predictive bottlenecks to create semantically structured latent actions for high-fidelity video world models.