Awesome World Models / arXiv

Text2World: Benchmarking Large Language Models for Symbolic World Model Generation

作者：作者信息待提取 · 单位：The University of Hong Kong, Shenzhen University, Harbin Institute of Technology, Shanghai AI Laboratory · 来源：General Approaches to World Models · 发布日期：2025 · 分类：4. Building World Models from Language Priors / LLM-in-the-loop World Generation

语言先验评测/基准视频生成
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