BeingBeyond

A startup company on foundation models for embodied intelligence.

[BeingBeyond @beingbeyond_]

In our pretraining, we mix egocentric human video with robot data, and Being-H0.7 is designed to support that joint pretraining setup. We do see some zero-shot ability already from the pretrained model. But if the goal is to push a downstream task as far as possible, we still do a very small second-stage finetuning on task-specific robot data. That said, human video is still the largest part of the whole training.

[BeingBeyond @beingbeyond_]

We believe human video is the most important path for robots to understand and interact with the physical world. Today we are introducing Being-H0.7, BeingBeyond’s third-generation flagship model. Being-H0.7 advances a new paradigm for world models built on latent-space reasoning, and scales pretraining to 200,000 hours of egocentric video. Check more about our work👇

Blog: https://t.co/2jXlYKWQUW
Paper: https://t.co/gWYA9nTR5d

[BeingBeyond @beingbeyond_]

Introducing BeingBeyond U1, the world’s first Real DexUMI.
U1 brings embodiment-agnostic dexterous hand data collection to real-world manipulation, taking a major step toward general-purpose dexterous manipulation models.
From data collection to transfer, deployment, and execution, U1 pushes UMI beyond the gripper era and into the age of dexterous hands.

[BeingBeyond @beingbeyond_]

Big month at BeingBeyond 🎉 We’re excited to share that in the past month we’ve had 8 papers accepted across top conferences and journals: CVPR’26 ×5, ICLR’26 ×1, ICRA’26 ×1, RAL ×1. Check our papers below👇

[CVPR'26] DemoFunGrasp: Universal Dexterous Functional Grasping via Demonstration-Editing Reinforcement Learning
https://t.co/DWtN5H8bnU
https://t.co/dSWcBq9Y2N

[CVPR'26] End-to-End Language-Action Model for Humanoid Whole Body Control
https://t.co/PixLZ3cn2p

[CVPR'26] Joint-Aligned Latent Action: Towards Scalable VLA Pretraining in the Wild
(To appear)

[CVPR'26] OpenT2M: No-frill Motion Generation with Open-source, Large-scale, High-quality Data
(To appear)

[CVPR'26] Spatial-Aware VLA Pretraining through Visual-Physical Alignment from Human Videos
https://t.co/jjbQO30PZi
https://t.co/M0IrByuUvf

[ICLR'26] DemoGrasp: Universal Dexterous Grasping from a Single Demonstration
https://t.co/7WP3C6Z4eZ
https://t.co/fUJiXjWYOB

[ICRA'26] Towards Proprioception-Aware Embodied Planning for Dual-Arm Humanoid Robots
https://t.co/qHfuoB63i5

[RAL] DemoHLM: From One Demonstration to Generalizable Humanoid Loco-Manipulation
https://t.co/ORrDeI8T3Z
https://t.co/v6wCTcmRYn

We’ll keep focusing on VLA models, Dexterous Manipulation, and Whole-Body Control. BeingBeyond looks forward to seeing everyone at the venues!🥳

[BeingBeyond @beingbeyond_]

@eddybuild Thx Eddy! Egocentric-10k is really a great help to the robotics community!🔥

[BeingBeyond @beingbeyond_]

@_akhaliq Check more details about our work👇
Blog: https://t.co/3IOgt7hrSv
Paper: https://t.co/7MsTj31JOE
Github: https://t.co/bvA5GmiyUK
Hugging Face: https://t.co/7TwQ8bHtSj

[BeingBeyond @beingbeyond_]

Thx @_akhaliq for sharing our work!🚀🚀We’re actively continuing to open-source the Being-H series. Weights and training scripts are already out, and we’ll be gradually releasing the training data soon. Hope this brings more value to the VLA community!

[AK @_akhaliq]

Being-H0.5

Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization

[BeingBeyond @beingbeyond_]

@_akhaliq Thx @_akhaliq for sharing our work!🚀📷We’re actively continuing to open-source the Being-H series. Weights and training scripts are already out, and we’ll be gradually releasing the training data soon. Hope this brings more value to the VLA community!

[BeingBeyond @beingbeyond_]

8/8
For more details, please check out our blog and paper. We've also open-sourced the training code and model weights, and we’ll continue releasing the training data over time, stay tuned. 👇
Blog🏠: https://t.co/L5lTXuyVpm
Paper📑: https://t.co/32FpsIR3Lb
Github💻: https://t.co/lEUsSZfwxH
Hugging Face🤗: https://t.co/nsnFLdHOBs

[BeingBeyond @beingbeyond_]

(thread 1/8) We're releasing Being-H0.5🔥🔥🔥: a foundation VLA model aimed at one big goal — cross-embodiment generalization. Instead of training a new brain for every robot, we want a single model to carry skills across bodies (arms, humanoids, dexterous hands). Here's an overview of Being-H0.5 👇

[BeingBeyond @beingbeyond_]

7/8
We deploy and evaluate across five very different real robots (upper-body humanoid, dexterous arm/hand, legged humanoid + hand, etc.). Across task suites (spatial / long-horizon / bimanual / generalization), Being-H0.5 performs strongly, with both specialist and single-checkpoint generalist variants. And we saw a surprising behavior we didn't want to oversell but couldn't ignore: embodiment-level zero-shot — the generalist checkpoint sometimes initiates qualitatively correct multi-step structure on previously unseen task–embodiment pairs in resembling environments.