DeepJEPA: Scaling World Models from Within
Overview
DeepJEPA is a new world model that scales computation internally by focusing on decision-critical transitions, outperforming or matching fixed-depth planners in robotics tasks.
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- arXiv Robotics — research abstractsDeepJEPA: Scaling World Models from Within
This research introduces DeepJEPA, a weight-tied joint-embedding predictive world model that scales computation internally by focusing on decision-critical transitions. It outperforms or matches fixed-depth planners in five visual-control settings while using fewer updates per transition, demonstrating that strategic allocation of internal computation improves planning without requiring uniform state decodability.
Event attention history
Current attention 3·Peak within the comparable range 9（2026-10-02 06:00 UTC）·Change within the comparable range over 24 hours -49%
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