What Drives Success in Physical Planning with Joint-Embedding Predictive World Models?
ResearchAI 90
Source: arXiv cs.AIPublish time unverified
arXiv:2512.24497v4 Announce Type: replace Abstract: A long-standing challenge in AI is to develop agents capable of solving a wide range of physical tasks and generalizing to new, unseen tasks and environments. A popular recent approach involves training a world model from state-action trajectories and subsequently use it with a planning algorithm to solve new tasks.