A Unifying Perspective on Causal World Models: From Observations to Representations to Structure
World Models (WM) are increasingly seen as a foundation for intelligent agents that can predict, plan, and act beyond their training distribution. In this paper, we study WMs from a causal perspective across multiple levels of abstraction, ranging from perceptual observations to building a conceptual representation of the structure governing the environment dynamics. We argue that useful WMs must go beyond generative capabilities alone: they should also capture entity properties, entity-to-entity interactions, and entity-to-environment interactions that determine and explain the dynamics of a
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- LinkedLinked via arxiv author · 85%Avinash Kori →
“A Unifying Perspective on Causal World Models: From Observations to Representations to Structure”
- LinkedLinked via arxiv author · 85%Fabrizio Russo →
“A Unifying Perspective on Causal World Models: From Observations to Representations to Structure”