DeepJEPA: Scaling World Models from Within
DeepJEPA addresses how to scale world models by focusing computation internally rather than just rolling farther. It introduces a method where the model decides whether to perform deeper latent updates for each potential future based on its expected value to the planner. This means refinement is concentrated only on critical events, like physical contact, leading to better performance without uniformly increasing prediction depth.