Author

Yifan Zhang

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Preprint Aug 2026

Mind-VLA: Instruction-Aware Spatial Representation Alignment for Vision-Language-Action Models

Mind-VLA is presented, an instruction-aware spatial representation alignment method for VLA models that obtains the target object specified by the language instruction, then prepares its canonical target views and extracts the corresponding VAE and VGGT features to enable instruction-aware 3D understanding.

Xing-Yu Ding, Yu-Zhong Zhao, Yang Wu et al. · 2 citations

Preprint Aug 2026

Temporal Forcing: 4D Representation Alignment for Vision-Language-Action Models

This work introduces a history pathway that enables a vanilla VLA model to summarize observation history into temporally aware latent representations, which captures the evolving 3D world through temporally consistent geometric representations, enabling a deeper understanding of dynamic environments.

Xing-Yu Ding, Yu-Zhong Zhao, Chun-Ming Zhao et al. · 1 citation