EWAM: An Enhanced World Action Model for Closed-Loop Online Adaptation in Embodied Intelligence
In this paper, we propose the Enhanced World Action Model (EWAM), a closed-loop online adaptation architecture built upon a pretrained and fully frozen Cosmos3 backbone network. Evaluated entirely under a zero-shot task protocol, EWAM is centrally focused on reducing the amount of additional deployment data required to adapt to new task layouts. Notably, no extra task-specific demonstration sets were introduced in any of the evaluations, and no fine-tuning was performed on the backbone network. Its performance gains stem entirely from an inference-time co-reasoning mechanism composed of four inserted lightweight neural layers: the Neural Experience Memory Layer located in the intermediate...
| Authors | Xin Zhou, Cong Miao |
|---|---|
| Primary category | cs.RO |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
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