light-loco-parkour

Light Loco Parkour - (wip)

Implementation of Light Loco Parkour, Versatile Perceptive Whole-Body Locomotion via Multi-Skill Distillation, out of Light Origins Labs

Citations

@article{chen2026light,
    title   = {Light-Loco-Parkour: Versatile Perceptive Whole-Body Locomotion via Multi-Skill Distillation},
    author  = {Chen, Hongming and Li, Zhuoran and Wang, Hongxi and Hu, Jiangpeng and Li, Ziliang and Liu, Peize and Zhao, QingRui and Liu, Xuhao and Pan, Liang and Lyu, Ximin and others},
    journal = {arXiv preprint arXiv:2608.02653},
    year    = {2026}
}

@inproceedings{
    mysore2022multicritic,
    title  = {Multi-Critic Actor Learning: Teaching {RL} Policies to Act with Style},
    author = {Siddharth Mysore and George Cheng and Yunqi Zhao and Kate Saenko and Meng Wu},
    booktitle = {International Conference on Learning Representations},
    year   = {2022},
    url    = {https://openreview.net/forum?id=rJvY_5OzoI}
}

@article{zhao2025knowledge,
    author  = {Zhao, Rui and Fan, Yuze and Li, Yun and Zhang, Dong and Gao, Fei and Gao, Zhenhai and Yang, Zhengcai},
    title   = {Knowledge Distillation-Enhanced Behavior Transformer for Decision-Making of Autonomous Driving},
    journal = {Sensors},
    year    = {2025},
    volume  = {25},
    number  = {1},
    pages   = {191},
    doi     = {10.3390/s25010191},
    url     = {https://www.mdpi.com/1424-8220/25/1/191}
}

@inproceedings{Huang2025TheGI,
    title   = {The GAN is dead; long live the GAN! A Modern GAN Baseline},
    author  = {Yiwen Huang and Aaron Gokaslan and Volodymyr Kuleshov and James Tompkin},
    year    = {2025},
    url     = {https://api.semanticscholar.org/CorpusID:275405495}
}

@misc{schwarzer2021dataefficientreinforcementlearningselfpredictive,
      title={Data-Efficient Reinforcement Learning with Self-Predictive Representations},
      author={Max Schwarzer and Ankesh Anand and Rishab Goel and R Devon Hjelm and Aaron Courville and Philip Bachman},
      year={2021},
      eprint={2007.05929},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2007.05929},
}

@misc{teoh2026nextlatentpredictiontransformerslearn,
      title={Next-Latent Prediction Transformers Learn Compact World Models},
      author={Jayden Teoh and Manan Tomar and Kwangjun Ahn and Edward S. Hu and Tim Pearce and Pratyusha Sharma and Akshay Krishnamurthy and Riashat Islam and Alex Lamb and John Langford},
      year={2026},
      eprint={2511.05963},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2511.05963},
}

Metadata

Release files for light-loco-parkour 0.0.32

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Source distribution (sdist)

Source distribution for light-loco-parkour 0.0.32
File	Size	Uploaded
light_loco_parkour-0.0.32.tar.gz	19.0 kB	Sep 24, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for light-loco-parkour 0.0.32
File	Interpreter	ABI	Platform	Reset
light_loco_parkour-0.0.32-py3-none-any.whl 18.3 kB Sep 24, 2026	Python 3	none	any	Details

Total release size: 37.3 kB

Release files / light_loco_parkour-0.0.32.tar.gz

Download URL	light_loco_parkour-0.0.32.tar.gz
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Release files / light_loco_parkour-0.0.32-py3-none-any.whl

Download URL	light_loco_parkour-0.0.32-py3-none-any.whl
Size	18.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`6be2b863798032e1bd30bada82111f541c0055bdf94460dd3b800fece9bc15d8`
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Upload date	Sep 24, 2026
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Uploaded via	`uv/0.8.17`