World Model Interpretability: From Decoding Representations to Understanding Latent Worlds

Key points

• Yet their latent worlds naturally lack a human-interpretable interface.1
• In this Perspective, we argue that as JEPA latents become internal states for prediction and action, interpretability must move beyond what they encode to how latent variables interact, evolve, and causally drive prediction.1
• Within our framework, existing JEPA interpretability efforts provide early evidence for Ground, while systematic analysis of latent structure, causal verification, and intervention remains largely unexplored.1
• Overall, this Perspective aims to call for a broader latent-world interpretability agenda that shifts attention from decoding representations toward understanding, validating, and acting on latent worlds.1

Sources (2)

• [1]World Model Interpretability: From Decoding Representations to Understanding Latent Worlds
  Hugging Face Daily Papers · Oct 18, 12:00 AM

  Emerging Joint-Embedding Predictive Architectures (JEPAs) are moving beyond representation learning towards latent world models that support prediction, planning, and control.

  Yet their latent worlds naturally lack a human-interpretable interface.

• [2]World Model Interpretability: From Decoding Representations to Understanding Latent Worlds
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 18, 02:29 PM · same content

Extractive summary: sentences quoted from the sources.