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| Spatial Semantic Enhancement | Manipulation Generalization |
|---|---|
| To address the requirements for instruction comprehension and spatial understanding in manipulation tasks, the model deeply integrates textual instructions with 2D/3D spatial details through continued pre-training, substantially strengthening its spatial perception and geometric understanding capabilities. | By leveraging full dynamics prediction data, the model achieves strong generalization across diverse manipulation tasks. In real-robot validation, it can complete 12 categories of complex manipulation tasks with high quality using only a single policy. |
@misc{unifolm-vla-0,
author = {Unitree},
title = {UnifoLM-VLA-0: A Vision-Language-Action (VLA) Framework under UnifoLM Family},
year = {2026},
}