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Long-horizon agents can now achieve GPT-6 Astra and Claude Opus-level performance on complex tasks by learning from dense, progressive rewards derived from latent world specifications.
WorldCrafter is a video world model that learns a camera-queryable implicit 3D-aware memory that enables streaming scene exploration from a single input image or text prompt and shows substantial gains in long-horizon consistency and camera-control accuracy while preserving visual quality during minute-scale exploration.
Injecting 6D Plucker coordinates into video transformers can drastically improve 3D consistency and camera control in generated videos.
