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README.md

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+---
+license: apache-2.0
+tags:
+- robotics
+- robot-manipulation
+- flow-matching
+- diffusion
+- reinforcement-learning
+- robomimic
+- one-step-inference
+pipeline_tag: robotics
+---
+
+# DM1: MeanFlow with Dispersive Regularization for 1-Step Robotic Manipulation
+
+<div align="center">
+
+[![Paper](https://img.shields.io/badge/Paper-arXiv-red)](https://arxiv.org/abs/2510.07865)
+[![Code](https://img.shields.io/badge/Code-GitHub-black)](https://github.com/Guowei-Zou/dm1-release)
+[![Project Page](https://img.shields.io/badge/Project-Page-blue)](https://guowei-zou.github.io/dm1/)
+
+</div>
+
+## Model Description
+
+DM1 is a novel flow matching framework for robotic manipulation that achieves **one-step inference** while maintaining high success rates. The model prevents representation collapse through dispersive regularization while achieving **20-40× faster inference** compared to diffusion baselines.
+
+### Key Features
+
+- ⚡ **Single-Step Inference**: 0.07s per timestep (vs. 2-3.5s for diffusion)
+- 🎯 **High Success Rates**: 10-20% improvement over diffusion baselines
+- 🔧 **Dispersive Loss Family**: InfoNCE, Cosine, Hinge regularizers
+- 👁️ **Vision-Ready**: Multi-view RGB observation support
+- 🤖 **Real Robot Validated**: Tested on Franka-Emika-Panda
+
+## Model Variants
+
+This repository contains pretrained weights for multiple configurations:
+
+| Variant | Description | Best For |
+|---------|-------------|----------|
+| ShortCut + InfoNCE L2 | Flow matching with L2-based dispersive loss | General tasks |
+| ShortCut + InfoNCE Cosine | Flow matching with cosine similarity | Vision tasks |
+| ShortCut + Hinge | Flow matching with hinge loss | Robust control |
+| ShortCut + Covariance | Flow matching with covariance regularization | Feature diversity |
+| MeanFlow variants | Mean flow baseline and dispersive versions | Fast inference |
+| ReFlow variants | Reflow baseline | Iterative refinement |
+
+## Supported Tasks
+
+- **Robomimic (RGB)**: lift, can, square, transport
+- **Franka Kitchen**: partial, complete, mixed
+- **D3IL**: avoiding, pushing, sorting
+
+## Quick Start
+
+### Installation
+
+```bash
+git clone https://github.com/Guowei-Zou/dm1-release.git
+cd dm1-release
+conda create -n dm1 python=3.8 -y
+conda activate dm1
+pip install -e .
+```
+
+### Download Checkpoints
+
+```python
+from huggingface_hub import hf_hub_download
+
+# Download specific checkpoint
+checkpoint = hf_hub_download(
+    repo_id="zougw2025/dm1-pretrained",
+    filename="checkpoints/w_0p1/can/can_w0p1_05_shortcut_infonce_cosine.pt"
+)
+```
+
+### Evaluation
+
+```bash
+python script/run.py \
+  --config-dir=cfg/robomimic/eval/can \
+  --config-name=eval_shortcut_mlp_img \
+  base_policy_path=checkpoints/w_0p1/can/can_w0p1_05_shortcut_infonce_cosine.pt
+```
+
+## Performance Metrics
+
+| Task | Baseline (32-128 steps) | DM1 (5 steps) | Improvement | Speedup |
+|------|-------------------------|---------------|-------------|---------|
+| Lift | ~85% | 99% | +14% | 20-40× |
+| Can | Variable | High | +10-20% | 20-40× |
+| Square | Moderate | Improved | +15-25% | 20-40× |
+| Transport | Low | High | +20-30% | 20-40× |
+
+## Citation
+
+If you use DM1 in your research, please cite:
+
+```bibtex
+@misc{zou2025dm1meanflowdispersiveregularization,
+      title={DM1: MeanFlow with Dispersive Regularization for 1-Step Robotic Manipulation},
+      author={Guowei Zou and Haitao Wang and Hejun Wu and Yukun Qian and Yuhang Wang and Weibing Li},
+      year={2025},
+      eprint={2510.07865},
+      archivePrefix={arXiv},
+      primaryClass={cs.RO},
+      url={https://arxiv.org/abs/2510.07865},
+}
+```
+
+## License
+
+This project is licensed under the Apache License 2.0.
+
+## Acknowledgments
+
+DM1 builds upon prior work including Diffusion Policy, ReinFlow, MeanFlow, FlowPolicy, D2PPO, and π0.5.
+
+## Contact
+
+- **Author**: Guowei Zou
+- **GitHub**: [dm1-release](https://github.com/Guowei-Zou/dm1-release)
+- **Project Page**: [https://guowei-zou.github.io/dm1/](https://guowei-zou.github.io/dm1/)