DiG-Flow: Discrepancy-Guided Flow Matching for Robust VLA Models

Wanpeng Zhang^1,2, Ye Wang^2,3, Hao Luo^1,2, Haoqi Yuan^1,2, Yicheng Feng^1,2,
Sipeng Zheng², Qin Jin³, Zongqing Lu^1,2†

¹Peking University    ²BeingBeyond    ³Renmin University of China

intro.mp4

DiG-Flow is a plug-and-play module for flow-matching based VLAs that rebalances control between the autoregressive foundation model and the flow expert. It embeds model inputs and flow outputs into a unified discrepancy space and uses this signal to gate the flow path, preventing shortcut transports that bypass the pretrained model and steering the expert toward more general, robust actions. DiG-Flow integrates seamlessly into diverse VLA architectures, including π, GR00T, and Being-H.

News

• [2025-12-01]: We publish DiG-Flow! Check our paper here. Code is coming soon! 🔥🔥🔥

Citation

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@article{zhang2025digflow,
  title={DiG-Flow: Discrepancy-Guided Flow Matching for Robust VLA Models},
  author={Zhang, Wanpeng and Wang, Ye and Luo, Hao and Yuan, Haoqi and Feng, Yicheng and Zheng, Sipeng and Jin, Qin and Lu, Zongqing},
  journal={arXiv preprint arXiv:2512.01715},
  year={2025}
}