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No physics engine is uniformly faithful, with critical failures in simulating impulsive contact and rapid textile motion revealed by the GAUGE benchmark.
A unified definition of world models could catalyze breakthroughs across AI subfields by clarifying what these internal simulators should predict and how they should be constructed.
Achieve superior CT-MRI cervical spine registration by adaptively fusing Mamba-based global context with Swin Transformer-based local detail.
Forget painstakingly collecting real-world data for deformable object manipulation: SIM1 achieves equivalent policy performance with 15x less data by grounding simulations in the physical world.
Zero-shot visuotactile policies trained in a fast, parallelized simulator can directly control real robots in contact-rich tasks.
