Author

Xin Shi

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Preprint Aug 2026

DreamWAM: Beyond RGB Future Prediction for World Action Models

DreamWAM is introduced, which reformulates future prediction as structured world modeling beyond RGB, representing future states through complementary views of appearance, motion, geometry, and semantics, showing that robust world-action learning depends not only on predicting the future, but on representing it in a fo...

Shanglin Yuan, Weiheng Zhao, Xin Shi et al. · 4 citations

Preprint Aug 2026

Faster-WAM: Efficient Inference-Time Future Conditioning for Robust World Action Models

Faster-WAM introduces a sparse future-conditioning framework that computes future representations once and selectively reuses them throughout action denoising, and proposes SparseMoT to replace ubiquitous layer-wise fusion with selective video-action interaction at a compact subset of network stages, and Interval KV-Fu...

Weiheng Zhao, Haoyi Jiang, Xin Shi et al. · 10 citations