The core of our framework is Group Relative Agent Optimization (GRAO), a novel meta-learning strategy that learns from historical optimization experiences.

WorldMark establishes a standardized benchmark for evaluating interactive video generation models with unified controls, identical scenarios, and comprehensive evaluation metrics across multiple model architectures.