Author

Jianjun Zhang

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Jul 2026

DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation

DSWAM is introduced, a Dual-System World Action Foundation Model for fine-grained robot manipulation and built and evaluated under the DeMaVLA real-world deformable manipulation setting with matched robot platform, pretraining data, post-training data, and evaluation criteria.

Jian Zhu, Jianjun Zhang, Taiyi Su et al. · arXiv.org · 2 citations

Preprint Jul 2026

Learning 4D Geometric Priors for Inference-Efficient World Action Models

MECo-WAM is proposed, a Multi-Expert Co-Training World Action Model that injects action-relevant 4D geometric priors into video-action representations while preserving the original lightweight inference graph.

Jianjun Zhang, Jian Zhu, Taiyi Su et al. · 5 citations