4 papers · 1 filter
RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model
Kehan Li, Bohan Hou, Minghao Zhu +28
We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and physically grounded framework, Ry…
RynnWorld-Teleop: An Action-Conditioned World Model for Digital Teleoperation
Haoyu Zhao, Xingyue Zhao, Hangyu Li +6
Scaling robot learning requires massive, diverse trajectory data, yet collection is currently bottlenecked by physical teleoperation, where every demonstration binds operator time…
EchoVLA: Robotic Vision-Language-Action Model with Synergistic Declarative Memory for Mobile Manipulation
Min Lin, Xiwen Liang, Bingqian Lin +12
Recent progress in Vision-Language-Action (VLA) models has enabled embodied agents to interpret multimodal instructions and perform complex tasks. However, existing VLAs are mostly…
RynnVLA-002: A Unified Vision-Language-Action and World Model
Jun Cen, Siteng Huang, Yuqian Yuan +11
We introduce RynnVLA-002, a unified Vision-Language-Action (VLA) and world model. The world model leverages action and visual inputs to predict future image states, learning the un…