SOURCE-LINKED INTELLIGENCE
OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining
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 training data are tightly coupled, obscuring which design choices matter and why. We introduce OpenWAM, an open research stack that turns world-action pretraining into a controlled experimental program. OpenWAM-Infra factorizes the WAM design space into composable modules with unified training, infere
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-07T12:12:32.000Z
First collected: 2026-09-20T20:52:10.320Z. This is not the publication date.