# ARPG scales dexterous manipulation via action representation pretraining

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/c8rnpomohh2cisqxcdlfsswyr
- Original: https://arxiv.org/abs/2610.34453

## Summary

ARPG proposes separating action representation learning from action generation: first pretrain an action representation encoder on large-scale human manipulation data, then freeze that encoder and train a 130M-parameter generative backbone in its representation space to learn task-conditioned action distributions.