Aim Short to Reach Far: Your Frozen World Model Can Plan Better Than You Think
cs.LG, cs.RO
Submitted: 2026-09-24
Updated: 2026-09-30
Terminology
Sources
- V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
- LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
- Mind the Gap: Promises and Pitfalls of Hierarchical Planning in LeWorldModel
- Latent World Models with Monotone Planning Costs for Image-Goal Navigation
- SAGE: Subgoal-Conditioned Action Generation for Latent World Model Planning
- Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control
- IMWM: Intuition Models Complement World Models for Latent Planning
- TD-MPC2: Scalable, Robust World Models for Continuous Control
- LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
- The Objective Is the Bottleneck: Latent World Models Encode What Their Planners Cannot Use
- Hierarchical Planning with Latent World Models
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