World Model Interpretability: From Decoding Representations to Understanding Latent Worlds

A Perspective article argues that Joint-Embedding Predictive Architectures (JEPA) are moving from representation learning toward latent world models that support prediction, planning, and control, and that interpretability research must shift from "what is encoded" to how latent variables interact, evolve, and causally drive prediction.