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Ethan Q. Chen

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Preprint Aug 2026

WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression

WALL-SS is introduced, a world model that generates visual futures through Scale-wise autoregressive Scaling, enabling action-controllable and long-horizon robotic simulation, and consistently benefits from on-policy alignment in reducing action drift and long-horizon inconsistency.

Maeve Zhang, Rainy Sun, Xiang Wang et al. · 0 citations

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