RoleWorld: Knowledge Transfer in World Modeling with Functional Role Abstractions

RoleWorld is a symbolic world‑modeling framework that uses reusable prototypes and environment‑specific parameters—called functional role abstractions—to capture how objects behave in interactions. A teacher LLM extracts role prototypes and executable transition rules from interaction trajectories, while an actor LLM employs a skill to apply these roles during decision making. In target environments, the actor refines role assignments and parameter estimates online through active testing, without updating LLM weights, and experiments on the MARS benchmark demonstrate robust generalization across environments with altered object behavior.