OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining
- Published
- Source
- arXiv
- Paper number
- 1075
- Field
- Robotics
- arXiv ID
- 2609.07398
Key points
- OpenWAM-Infra breaks the design space of world and action models into modules and integrates training, inference, deployment, and evaluation.
- Controlled experiments disentangle the roles of generative models and compact representations, what information flows from world prediction to action, and the effect of joint training.
- Models trained on roughly 6,400 hours of egocentric human and robot data were evaluated on eight simulation benchmarks and real robot manipulation.
- Because design and evaluation conditions are shared, others can reproduce component swaps and compare robot-learning methods on the same footing.
- The abstract's performance claims were verified only for the evaluated single-arm and bimanual manipulation settings, not for every robot environment.
Paper links
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