OpenWAM, an open and modular framework for systematic world-action model pretraining, was introduced to address the monolithic nature of existing systems by separating the generative backbone, visual representation, architecture, information flow, inference procedure, and training components. The framework aims to inherit world knowledge from video-generative priors and channel it into executable control signals through embodied experience, offering a more flexible and systematic approach for developing world-action models.
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are monolithic: the generative backbone, visual representation, architecture, information flow, inference procedure, and tr
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