Ethan-pooh/pact

PACT Data and Checkpoints

This repository hosts the data and pretrained policy checkpoints for PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation.

PACT is a self-evolving post-training framework for aligning pretrained diffusion policies with physical safety constraints in embodied manipulation. It uses self-rollouts and automatically computed physical constraints to distill constraint gradients into diffusion policies, improving safety without requiring demonstrations, task rewards, interventions, or outcome annotations.

**Website** - **GitHub** - **Paper**

Table of Contents

• —Highlights
• —Repository Contents
• —Quickstart
• —Expected Directory Layout
• —Intended Uses and Limitations
• —Changelog
• —Citation
• —Contact

Highlights

• —Self-evolving: Aligns diffusion policies from self-rollouts without demonstrations, interventions, rewards, or outcome annotations.
• —Efficient optimization: Distills constraint gradients into the policy, providing dense supervision across diffusion timesteps.
• —Curriculum alignment: Progressively tightens constraints to preserve task competence while improving safety.
• —Foundation-model compatible: Plugs into diffusion-based policies, including flow policies, VLAs, and WAMs, without architecture modifications.
• —Theoretical control: Bounds policy shift and supports monotone improvement.
• —Proven in practice: Improves both task success and safety across simulation and real-world manipulation.

Repository Contents

This Hugging Face dataset repository contains file-based assets used by the official PACT codebase:

• —Pretrained base policy checkpoints for Diffusion Policy on RoboTwin tasks.
• —Pre-generated instruction datasets used during PACT post-training.
• —Shared environment metadata required by the released instruction data.

The released task set includes:

• —handover_apple
• —handover_block
• —pick_diverse_bottles
• —pick_dual_bottles
• —place_dual_shoes
• —pour_water_to_cup
• —stack_blocks_two

This repository is intended for file-based download and use with the official GitHub codebase. The Hugging Face dataset viewer is not the primary interface for these assets.

Quickstart

Install Git LFS if needed, then download the repository:

git lfs install
git clone https://huggingface.co/datasets/Ethan-pooh/pact

Alternatively, download with the Hugging Face CLI:

huggingface-cli download Ethan-pooh/pact \
  --repo-type dataset \
  --local-dir ./pact_hf

The instruction data is provided as data.tar.gz. Untar it and place the extracted files under the PACT repository:

mkdir -p /path/to/PACT/data
tar -xzf ./pact_hf/data.tar.gz -C /path/to/PACT/data

Please refer to the official PACT GitHub repository for installation, post-training, and evaluation commands.

Expected Directory Layout

After downloading, place the pretrained base policy checkpoints under the PACT repository as follows:

PACT/policy/DP/checkpoints/
├── handover_apple-demo_randomized-200-0/600.ckpt
├── handover_block-demo_randomized-200-0/600.ckpt
├── pick_diverse_bottles-demo_randomized-200-0/600.ckpt
├── pick_dual_bottles-demo_randomized-200-0/600.ckpt
├── place_dual_shoes-demo_randomized-200-0/600.ckpt
├── pour_water_to_cup-demo_randomized-200-0/600.ckpt
└── stack_blocks_two-demo_randomized-200-0/600.ckpt

After untarring data.tar.gz, the pre-generated instruction dataset and shared environment metadata should follow this structure:

PACT/data/
├── data/handover_apple/demo_randomized/instructions
├── data/handover_block/demo_randomized/instructions
├── data/pick_diverse_bottles/demo_randomized/instructions
├── data/pick_dual_bottles/demo_randomized/instructions
├── data/place_dual_shoes/demo_randomized/instructions
├── data/pour_water_to_cup/demo_randomized/instructions
├── data/stack_blocks_two/demo_randomized/instructions
└── env_meta.pkl

Once the files are arranged, evaluate a base policy with:

cd policy/DP
bash eval_dr.sh pick_dual_bottles demo_randomized demo_randomized 200 0 600 0

Run PACT post-training from the repository root with:

CUDA_VISIBLE_DEVICES=0,1,2,3 bash policy/DP/on_policy_distill_multigpu.sh pick_dual_bottles onpolicy_randomized 200 0 14

Intended Uses and Limitations

Intended uses

• —Research on robot manipulation, diffusion policies, and physical safety alignment.
• —Reproducing the PACT post-training pipeline on RoboTwin tasks.
• —Evaluating pretrained base policies and post-trained PACT policies using the official codebase.

Limitations

• —The checkpoints and instruction data are tied to the released RoboTwin task configurations.
• —Post-training depends on correct installation of RoboTwin, Diffusion Policy, PACT cost functions, and task assets.
• —Results may vary with simulator version, asset placement, random seeds, and the implemented physical constraint functions.

Safety and responsible use

• —These assets are intended for simulation-based research in RoboTwin.
• —Do not interpret simulated safety improvements as a direct guarantee of real-world robot safety without additional validation.

Changelog

• —2026-06: Initial release of PACT data and pretrained base policy checkpoints on Hugging Face.

Citation

If you find this dataset, checkpoints, or codebase useful, please cite:

@article{wu2026pact,
  title={PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation},
  author={Wu, Lingxuan and Zhu, Zijian and Wang, Lizhong and Ying, Chengyang and Chen, Huayu and Yang, Xiao and Liu, Fangming and Zhu, Jun},
  journal={arXiv preprint arXiv:2606.08414},
  year={2026}
}

Contact

• —Project page: https://ethan-iai.github.io/pact/
• —Paper: https://arxiv.org/abs/2606.08414
• —GitHub: https://github.com/thu-ml/PACT
• —Hugging Face: https://huggingface.co/datasets/Ethan-pooh/pact