CAS Industrial AI Institute's World Model PAIWorld Tops WorldArena Leaderboard

The WorldArena international authoritative leaderboard for world models has recently updated its rankings. The Physical AI Lab (The PAI Lab), led by researcher Xu Kai from the Institute of Industrial Artificial Intelligence, Chinese Academy of Sciences, has topped the list with a total score of 72.31 for its self-developed world model PAIWorld. The leaderboard covers six dimensions: visual quality, motion quality, content consistency, physical adherence, 3D accuracy, and controllability, featuring top global teams including WorldLab led by Fei-Fei Li, Google, NVIDIA, Stanford University, and Zhiyuan Robot.

Key Metric Performance

• Motion Smoothness: 95.41 points, ranking among the top, demonstrating advantages in spatiotemporal consistency.
• Trajectory Accuracy: Leading the second place by 7.4 points, maintaining accurate trajectories in long-term predictions.

Technical Highlights

PAIWorld is centered on "geometric prior-driven + multi-view spatiotemporal joint modeling":

• 3D Geometric Prior Injection: Embedding depth structure, surface geometry, and occlusion relationships as explicit constraints into the generation process via 3D foundation models.
• Geometric Rotary Position Encoding (Geo-RoPE): Splitting attention heads into ray subspace and pose subspace to encode 3D ray direction and camera pose information.
• Multi-View Attention Mechanism: Aligning geometric and appearance information of the same physical scene across views in the video generation network.

Recent Achievements and Future Plans

• An earlier version won second place in the world model track of the AGIBOT WORLD CHALLENGE @ ICRA 2026 and secured first place in the "scene consistency" category.
• The team plans to leverage its self-developed world model and World Action Model to create an embodied data loop, enabling self-improvement and continuous evolution.