2026
Enfold: Folding World-Generator Computation into Predictive Representations for Efficient Embodied Control
Wei-Li Zeng, Yi-Tong Xing, Fu-Long Liu et al.
· arXiv.org · 0 citations
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Preprint
Jul 2026
Enfold: Folding World Model Imagination into Predictive Representations for Ultra-Efficient Embodied Control
This work presents Enfold, which transfers this computation that constructs a future into a representation predicted from the current visual context and language instruction, and recast a world generator as a source of predictive control representations if its internal structure can be enfolded into the present.
Wei-Li Zeng, Yi-Tong Xing, Fu-Long Liu et al.
· 1 citation
Preprint
Aug 2026
Spatiotemporally Decoupled Autoregressive Diffusion Model for Human Motion Generation
A unified spatiotemporally decoupled framework named DeMoDiff is proposed, which jointly redesigns representation and architecture and incorporates spatial-temporal masking and attention mechanisms into an autoregressive diffusion generator, achieving both generative capability and controllable editability.
Chengqun Yang, Liang Xu, Yanping Li et al.
· 0 citations