OpenWorldLib：先進世界模型的統一程式碼庫與定義

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models

April 6, 2026

作者: DataFlow Team, Bohan Zeng, Daili Hua, Kaixin Zhu, Yifan Dai, Bozhou Li, Yuran Wang, Chengzhuo Tong, Yifan Yang, Mingkun Chang, Jianbin Zhao, Zhou Liu, Hao Liang, Xiaochen Ma, Ruichuan An, Junbo Niu, Zimo Meng, Tianyi Bai, Meiyi Qiang, Huanyao Zhang, Zhiyou Xiao, Tianyu Guo, Qinhan Yu, Runhao Zhao, Zhengpin Li, Xinyi Huang, Yisheng Pan, Yiwen Tang, Yang Shi, Yue Ding, Xinlong Chen, Hongcheng Gao, Minglei Shi, Jialong Wu, Zekun Wang, Yuanxing Zhang, Xintao Wang, Pengfei Wan, Yiren Song, Mike Zheng Shou, Wentao Zhang

cs.AI

摘要

世界模型作為人工智慧領域中頗具前景的研究方向已獲得廣泛關注，但目前仍缺乏清晰統一的定義。本文提出OpenWorldLib——一個面向先進世界模型的綜合性標準化推理框架。基於世界模型的演進脈絡，我們給出明確定義：世界模型是以感知為核心、具備交互與長期記憶能力，用於理解與預測複雜世界的模型或框架。我們進一步系統化地歸納了世界模型的核心能力分類。基於此定義，OpenWorldLib將不同任務的模型整合至統一框架，實現高效復用與協同推理。最後，我們針對世界模型未來研究的潛在方向提出進一步的思考與分析。代碼連結：https://github.com/OpenDCAI/OpenWorldLib

English

World models have garnered significant attention as a promising research direction in artificial intelligence, yet a clear and unified definition remains lacking. In this paper, we introduce OpenWorldLib, a comprehensive and standardized inference framework for Advanced World Models. Drawing on the evolution of world models, we propose a clear definition: a world model is a model or framework centered on perception, equipped with interaction and long-term memory capabilities, for understanding and predicting the complex world. We further systematically categorize the essential capabilities of world models. Based on this definition, OpenWorldLib integrates models across different tasks within a unified framework, enabling efficient reuse and collaborative inference. Finally, we present additional reflections and analyses on potential future directions for world model research. Code link: https://github.com/OpenDCAI/OpenWorldLib