Skip to main content

Large Behavioral Model from Toyota Research

Project description

Screenshot 2025-07-10 at 5 12 49 PM

LBM - TRI (wip)

Implementation of the Large Behavioral Model architecture for dexterous manipulation from Toyota Research Institute.

Project Page

Data Normalization Takeaway

Install

$ pip install TRI-LBM

Usage

import torch
from TRI_LBM import LBM

lbm = LBM(
    action_dim = 20,
    dim_pose = 10
)

commands = ['pick up the apple and place in the blue tray']
images = torch.randn(1, 3, 3, 224, 224)
actions = torch.randn(1, 16, 20)
pose = torch.randn(1, 10)

loss = lbm(
    text = commands,
    images = images,
    pose = pose,
    actions = actions,
)

loss.backward()

# after much training

sampled_actions = lbm.sample(
    text = commands,
    images = images,
    pose = pose,
) # (1, 16, 20)

Citations

@misc{trilbmteam2025carefulexaminationlargebehavior,
    title  = {A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation}, 
    author = {TRI LBM Team and Jose Barreiros and Andrew Beaulieu and Aditya Bhat and Rick Cory and Eric Cousineau and Hongkai Dai and Ching-Hsin Fang and Kunimatsu Hashimoto and Muhammad Zubair Irshad and Masha Itkina and Naveen Kuppuswamy and Kuan-Hui Lee and Katherine Liu and Dale McConachie and Ian McMahon and Haruki Nishimura and Calder Phillips-Grafflin and Charles Richter and Paarth Shah and Krishnan Srinivasan and Blake Wulfe and Chen Xu and Mengchao Zhang and Alex Alspach and Maya Angeles and Kushal Arora and Vitor Campagnolo Guizilini and Alejandro Castro and Dian Chen and Ting-Sheng Chu and Sam Creasey and Sean Curtis and Richard Denitto and Emma Dixon and Eric Dusel and Matthew Ferreira and Aimee Goncalves and Grant Gould and Damrong Guoy and Swati Gupta and Xuchen Han and Kyle Hatch and Brendan Hathaway and Allison Henry and Hillel Hochsztein and Phoebe Horgan and Shun Iwase and Donovon Jackson and Siddharth Karamcheti and Sedrick Keh and Joseph Masterjohn and Jean Mercat and Patrick Miller and Paul Mitiguy and Tony Nguyen and Jeremy Nimmer and Yuki Noguchi and Reko Ong and Aykut Onol and Owen Pfannenstiehl and Richard Poyner and Leticia Priebe Mendes Rocha and Gordon Richardson and Christopher Rodriguez and Derick Seale and Michael Sherman and Mariah Smith-Jones and David Tago and Pavel Tokmakov and Matthew Tran and Basile Van Hoorick and Igor Vasiljevic and Sergey Zakharov and Mark Zolotas and Rares Ambrus and Kerri Fetzer-Borelli and Benjamin Burchfiel and Hadas Kress-Gazit and Siyuan Feng and Stacie Ford and Russ Tedrake},
    year   = {2025},
    eprint = {2507.05331},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url = {https://arxiv.org/abs/2507.05331}, 
}
@inproceedings{Wagenmaker2025SteeringYD,
    title   = {Steering Your Diffusion Policy with Latent Space Reinforcement Learning},
    author  = {Andrew Wagenmaker and Mitsuhiko Nakamoto and Yunchu Zhang and Seohong Park and Waleed Yagoub and Anusha Nagabandi and Abhishek Gupta and Sergey Levine},
    year    = {2025},
    url     = {https://api.semanticscholar.org/CorpusID:279464702}
}
@misc{heng2025vitacformerlearningcrossmodalrepresentation,
    title   = {ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation}, 
    author  = {Liang Heng and Haoran Geng and Kaifeng Zhang and Pieter Abbeel and Jitendra Malik},
    year    = {2025},
    eprint  = {2506.15953},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url     = {https://arxiv.org/abs/2506.15953}, 
}
@misc{cheang2025gr3technicalreport,
    title   = {GR-3 Technical Report}, 
    author  = {Chilam Cheang and Sijin Chen and Zhongren Cui and Yingdong Hu and Liqun Huang and Tao Kong and Hang Li and Yifeng Li and Yuxiao Liu and Xiao Ma and Hao Niu and Wenxuan Ou and Wanli Peng and Zeyu Ren and Haixin Shi and Jiawen Tian and Hongtao Wu and Xin Xiao and Yuyang Xiao and Jiafeng Xu and Yichu Yang},
    year    = {2025},
    eprint  = {2507.15493},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url     = {https://arxiv.org/abs/2507.15493}, 
}
@misc{PI2025,
    title = {VLAs that Train Fast, Run Fast, and Generalize Better},
    author = {Danny Driess, Jost Tobias Springenberg, Brian Ichter, Lili Yu, Adrian Li-Bell, Karl Pertsch, Allen Z. Ren, Homer Walke, Quan Vuong, Lucy Xiaoyang Shi, Sergey Levine},
    year   = {2025},
    url    = {https://www.physicalintelligence.company/research/knowledge_insulation}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tri_lbm-0.0.34.tar.gz (14.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tri_lbm-0.0.34-py3-none-any.whl (11.1 kB view details)

Uploaded Python 3

File details

Details for the file tri_lbm-0.0.34.tar.gz.

File metadata

  • Download URL: tri_lbm-0.0.34.tar.gz
  • Upload date:
  • Size: 14.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for tri_lbm-0.0.34.tar.gz
Algorithm Hash digest
SHA256 5bda09e3470afddde68612688987996f23049a5ea96a69c263dd5d5d2d764c2d
MD5 b8ec702eef2ee635b943ed2753ef8501
BLAKE2b-256 c8d838e86c93e9330f867a323cd87657f726e558d1100469b1e7ac1f876d5ca4

See more details on using hashes here.

File details

Details for the file tri_lbm-0.0.34-py3-none-any.whl.

File metadata

  • Download URL: tri_lbm-0.0.34-py3-none-any.whl
  • Upload date:
  • Size: 11.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for tri_lbm-0.0.34-py3-none-any.whl
Algorithm Hash digest
SHA256 b6bc61c84203c7fa9afdc2898a6ff81d42fde4c9ad058bbc668095ddb005945d
MD5 5a4254df042d9f127910f40ad1c22a14
BLAKE2b-256 ac0f0fbc7ed62b64fd0b2f2e1d552caa00659e3e3006d0b7c2c7cfac218dae92

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page