yuvansharma/arm4r-ckpts

Pre-training Auto-regressive Robotic Models with 4D Representations

by Dantong Niu*, Yuvan Sharma*, Haoru Xue, Giscard Biamby, Junyi Zhang, Ziteng Ji, Trevor Darrell†, and Roei Herzig†

^{*Equal contribution, †Equal advising}
Berkeley AI Research, UC Berkeley
ICML 2025

Paper • Code • Models • Dataset

This repository contains our checkpoints and is structured as follows:

.
├── .gitattributes
├── README.md
├── model_ckpts
│   ├── ft_kinova_pick_cube  # Single Task Policy for Real Kinova Setting for "pick cube" task
│   │   ├── ft_kinova_pick_cube.pth
│   │   └── run.yaml
│   ├── ft_rlbench_meat_off_grill # Single Task Policy for Sim RLBench Setting for "meat off grill" task
│   │   ├── ft_rlbench_meat_off_grill.pth
│   │   └── run.yaml
│   └── pretrained_epic # first stage 3D point pre-training model weights
│       ├── pretrained_epic.pth
│       └── run.yaml
└── vision_encoder
    └── cross-mae-rtx-vitb.pth

Citation

If you find our work helpful, please consider citing:

@article{niu2025pre,
  title={Pre-training auto-regressive robotic models with 4d representations},
  author={Niu, Dantong and Sharma, Yuvan and Xue, Haoru and Biamby, Giscard and Zhang, Junyi and Ji, Ziteng and Darrell, Trevor and Herzig, Roei},
  journal={arXiv preprint arXiv:2502.13142},
  year={2025}
}