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| license: mit | |
| pretty_name: Faster-WAM Checkpoints | |
| library_name: pytorch | |
| tags: | |
| - robotics | |
| - robot-learning | |
| - imitation-learning | |
| - embodied-ai | |
| - libero | |
| - robotwin | |
| # Faster-WAM Checkpoints | |
| This repository provides the official checkpoints for **[Faster-WAM: Efficient Inference-Time Future Conditioning for Robust World Action Models](https://arxiv.org/pdf/2608.04404)**. | |
| ## Files | |
| ```text | |
| libero/ | |
| βββ step_021700.pt | |
| βββ dataset_stats.json | |
| robotwin/ | |
| βββ step_029355.pt | |
| βββ dataset_stats.json | |
| ``` | |
| - `libero/step_021700.pt`: checkpoint for LIBERO and LIBERO-Plus evaluation. | |
| - `robotwin/step_029355.pt`: checkpoint for RoboTwin evaluation. | |
| - `dataset_stats.json`: dataset statistics required by the corresponding evaluation pipeline. | |
| ## Links | |
| - Code: [https://github.com/hustvl/FasterWAM](https://github.com/hustvl/FasterWAM) | |
| - Paper: [https://arxiv.org/pdf/2608.04404](https://arxiv.org/pdf/2608.04404) | |
| ## Citation | |
| ```bibtex | |
| @article{zhao2026faster, | |
| title = {Faster-WAM: Efficient Inference-Time Future Conditioning for Robust World Action Models}, | |
| author = {Zhao, Weiheng and Jiang, Haoyi and Shi, Xin and Liu, Liu and Huang, Fan and Su, Zhizhong and Sui, Wei and Wang, Xinggang}, | |
| journal = {arXiv preprint arXiv:2608.04404}, | |
| year = {2026} | |
| } | |
| ``` | |