DeltaWAM: Delta World Action Models for Bimanual Manipulation
World-action models (WAMs) transfer visual and motion priors from pretrained video generators to robot control by jointly modeling visual dynamics and actions. Existing WAMs, however, predict dense future frames during training, repeatedly modeling largely unchanged content and coupling action-conditioned dynamics to nuisance appearance variations. At inference, processing each complete observation with the heavy video expert bottlenecks few-step action generation. Accordingly, we propose DeltaWAM, which jointly predicts visual deltas and actions using dense-anchor, sparse-delta, and action streams, with three architectures that differ in representation and computation sharing. We further...
| Authors | Han Yan, Zishang Xiang, Haokai Jiang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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