5 papers
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
Learning Novel Skills from Language-Generated Demonstrations
Ao-Qun Jin, Tian-Yu Xiang, Xiao-Hu Zhou +8
Robots are increasingly deployed across diverse domains to tackle tasks requiring novel skills. However, current robot learning algorithms for acquiring novel skills often rely on…
MAGI-1: Autoregressive Video Generation at Scale
Sand. ai, Hansi Teng, Hongyu Jia +36
We present MAGI-1, a world model that generates videos by autoregressively predicting a sequence of video chunks, defined as fixed-length segments of consecutive frames. Trained to…
Learning Physics-Based Full-Body Human Reaching and Grasping from Brief Walking References
Yitang Li, Mingxian Lin, Zhuo Lin +3
Existing motion generation methods based on mocap data are often limited by data quality and coverage. In this work, we propose a framework that generates diverse, physically feasi…
BA-Net: Bridge Attention in Deep Neural Networks
Ronghui Zhang, Runzong Zou, Yue Zhao +5
Attention mechanisms, particularly channel attention, have become highly influential in numerous computer vision tasks. Despite their effectiveness, many existing methods primarily…