Author

Erwin Wu

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Preprint Oct 2026

SPW-Nav: A Streaming Panoramic World Model for Language-Guided Navigation

Language-guided panoramic video generation benefits various downstream applications, such as interactive 3D scene exploration, virtual reality experiences, and embodied agent training. Existing panoramic generators follow predefined trajectories, and interactive world models act through low-level actions in perspective...

Yun-Heng Liu, Zi-Qi Cai, Si-Qi Yang et al. · 0 citations

Preprint Sep 2026

World2Motion: Turning Video World Models into 3D Human Motion Generators

World2Motion, a framework that generates scene-aware 3D human motion and corresponding video from a single image and a text prompt, and proposes a shift-decoupled noise schedule that assigns different noise levels to video and motion through shared denoising progress, reducing motion jitter.

Fang-Yuan Tu, Xiang-Yue Zhang, Yi-Yi Cai et al. · 0 citations

Preprint Aug 2026

MASS: Multiplayer World Models with Authoritative Shared State

The results show that explicit, authoritative state modeling provides a practical foundation for scalable and consistent multi-agent world simulation.

Ziqi Cai, Si-Qi Yang, Yimu Wang et al. · 2 citations · ⚡1

#artificial intelligence Preprint Sep 2026

KaiNinja: Extending Native 3D Generators to the Part Level

KaiNinja, a part-level extension of TRELLIS.2 built on a dual-volume form of its O-Voxel representation, is the first 3D generative model trained on agent-authored part data and finds that whole-object fidelity improves over the same backbone fine-tuned on the same dataset.

Rui-Han Yu, Lian Fu, Mu-Yao Niu et al. · 0 citations