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DreamWAM: Beyond RGB Future Prediction for World Action Models
Shanglin Yuan, Weiheng Zhao, Xin Shi +6
World Action Models (WAMs) learn action-relevant representations by predicting how the observed world will evolve. Most existing WAMs define this future in RGB space, where task-re…
MotionVLA: Injecting Geometric Motion into Vision-Language-Action Model
Shanglin Yuan, Weiheng Zhao, Xianda Guo +4
Vision-language-action (VLA) models increasingly condition robot policies on history, depth, or 4D features to resolve ambiguity in long-horizon manipulation. However, more spatiot…
OmniTrack: General Motion Tracking via Physics-Consistent Reference
Yuhan Li, Peiyuan Zhi, Yunshen Wang +6
Learning motion tracking from rich human motion data is a foundational task for achieving general control in humanoid robots, enabling them to perform diverse behaviors. However, d…
M2Diffuser: Diffusion-based Trajectory Optimization for Mobile Manipulation in 3D Scenes
Sixu Yan, Zeyu Zhang, Muzhi Han +7
Recent advances in diffusion models have opened new avenues for research into embodied AI agents and robotics. Despite significant achievements in complex robotic locomotion and sk…
M3Bench: Benchmarking Whole-body Motion Generation for Mobile Manipulation in 3D Scenes
Zeyu Zhang, Sixu Yan, Muzhi Han +4
We propose M3Bench, a new benchmark for whole-body motion generation in mobile manipulation tasks. Given a 3D scene context, M3Bench requires an embodied agent to reason about its…
VAD: Vectorized Scene Representation for Efficient Autonomous Driving
Bo Jiang, Shaoyu Chen, Qing Xu +7
Autonomous driving requires a comprehensive understanding of the surrounding environment for reliable trajectory planning. Previous works rely on dense rasterized scene representat…