6 papers
RynnValue: Scaling Robotic Value Foundation Models with Temporal Distance
Dongchi Huang, Hongyin Zhang, Bohan Hou +12
General-purpose reward models are increasingly the bottleneck for scaling robot learning, yet the recipe for learning value-related capabilities from large-scale heterogeneous corp…
Data Pyramid for Embodied Manipulation: A Survey
Yifan Ye, Yankai Fu, Yaoxu Lv +26
Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations w…
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…
RynnBrain: Open Embodied Foundation Models
Ronghao Dang, Jiayan Guo, Bohan Hou +23
Despite rapid progress in multimodal foundation models, embodied intelligence community still lacks a unified, physically grounded foundation model that integrates perception, reas…
RF-MatID: Dataset and Benchmark for Radio Frequency Material Identification
Xinyan Chen, Qinchun Li, Ruiqin Ma +3
Accurate material identification plays a crucial role in embodied AI systems, enabling a wide range of applications. However, current vision-based solutions are limited by the inhe…
SkeFi: Cross-Modal Knowledge Transfer for Wireless Skeleton-Based Action Recognition
Shunyu Huang, Yunjiao Zhou, Jianfei Yang
Skeleton-based action recognition leverages human pose keypoints to categorize human actions, which shows superior generalization and interoperability compared to regular end-to-en…