Core Insights - The article discusses the need to redefine the evaluation of world models in embodied intelligence, emphasizing that visual quality does not equate to task effectiveness [5][26]. - The introduction of the "World-in-World" platform aims to assess world models through closed-loop interactions, focusing on their practical utility rather than just visual fidelity [6][26]. Evaluation of World Models - Current evaluation systems prioritize visual clarity and scene rationality, neglecting whether these models can assist agents in decision-making for real tasks [5][6]. - The platform introduces a closed-loop system that integrates observation, decision-making, execution, and re-observation, ensuring fair and practical assessments [6][7]. Model Compatibility and Decision-Making - A unified action API is established to standardize input across different world models, allowing them to process the same tasks effectively [7]. - The decision-making process is structured into three phases: proposal generation, simulation of outcomes, and selection of the optimal action based on task goals [8][13]. Experimental Findings - Experiments with 12 mainstream world models revealed that visual realism does not guarantee task success; instead, action alignment is crucial [18][20]. - Fine-tuning smaller models with task-specific data proved more effective than simply using larger pre-trained models, highlighting a cost-effective optimization strategy [21][23]. - Increasing computational effort for simulations significantly improved task success rates, suggesting that more extensive predictive modeling leads to better decision-making [23]. Limitations and Future Directions - While models excel in perception and navigation, they struggle with physical manipulation tasks due to a lack of physical modeling considerations [25]. - The article concludes that future developments should focus on enhancing controllability, utilizing task data for fine-tuning, and incorporating physical modeling to improve the practical application of world models in robotics [26].