# TTP: Human-Centric Transferable Tactile Pre-Training for Dexterous Robotic Manipulation [![Blog](https://img.shields.io/badge/Blog-TTP-green)](https://research.beingbeyond.com/ttp) [![Paper](https://img.shields.io/badge/arXiv-Paper-b31b1b.svg)](https://arxiv.org/pdf/2607.01067) [![Models](https://img.shields.io/badge/🤗%20Hugging%20Face-Models-yellow)](https://huggingface.co/BeingBeyond/TTP) [![Data](https://img.shields.io/badge/🤗%20Hugging%20Face-Data-orange)](https://huggingface.co/datasets/BeingBeyond/H-Tac_Sample) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](./LICENSE) ## Model Checkpoints and Datasets Download models from Hugging Face: | Model Type | Model Name | Description | |------------|------------|-------------| | **VLA Pre-trained** | [TTP-pretrained](https://huggingface.co/BeingBeyond/TTP/tree/main/pretrained) | Base vision-language-action model (preview) | | **VLA Post-trained** | [TTP-LIBERO](https://huggingface.co/BeingBeyond/TTP/tree/main/libero) | Post-trained on LIBERO benchmark | | **VLA Post-trained** | [TTP-LIBERO-plus](https://huggingface.co/BeingBeyond/TTP/tree/main/libero-plus) | Post-trained on LIBERO, zero-shot evaluated on LIBERO-plus | | **VLA Post-trained** | [TTP-RoboCasa](https://huggingface.co/BeingBeyond/TTP/tree/main/robocasa) | Post-trained on RoboCasa 24 tasks | The whole datasets of H-Tac will be coming soon. For now, you can download a small subset of H-Tac from Hugging Face for testing and evaluation: [H-Tac_Sample](https://huggingface.co/datasets/BeingBeyond/H-Tac_Sample) ## Setup ### Clone repository ```bash git clone https://github.com/BeingBeyond/TTP.git cd TTP ``` ### Create environment ```bash conda create -n beingh python=3.10 conda activate beingh ``` ### Install package ```bash pip install -r requirements.txt pip install flash-attn --no-build-isolation ``` ## Pre-Training ```bash bash scripts/train/train_human_tactile.sh ``` ## Post-Training ```bash bash scripts/train/train_libero_example.sh bash scripts/train/train_robocasa.sh ``` ## Evaluation ```bash bash scripts/eval/eval-libero-fast.sh bash scripts/eval/eval-libero-plus.sh bash scripts/eval/eval-robocasa-multiprocess.sh ``` ## Acknowledgments TTP builds on the following excellent open-source projects: - [InternVL](https://github.com/OpenGVLab/InternVL): Vision-Language model backbone - [Bagel](https://github.com/ByteDance-Seed/Bagel): Training framework - [Qwen](https://github.com/QwenLM/Qwen): Language model and MoE expert - [LIBERO](https://github.com/Lifelong-Robot-Learning/LIBERO): Benchmark for lifelong robot learning - [RoboCasa](https://github.com/robocasa/robocasa): Large-scale simulation benchmark for everyday tasks - [Being-H0.5](https://github.com/BeingBeyond/Being-H): Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization We thank the authors for their contributions to the robotics and machine learning communities. ## Citation If you find this work useful in your research, please consider citing us! ```bibtex @article{beingbeyond2026ttp, title={Human-Centric Transferable Tactile Pre-Training for Dexterous Robotic Manipulation}, author={Zhang, Chi and Cai, Penglin and Xi, Ziheng and Yuan, Haoqi and Luo, Hao and Zhang, Wanpeng and Zheng, Sipeng and Xu, Chaoyi and Lu, Zongqing}, journal={arXiv preprint arXiv:2607.01067}, year={2026} } ```