How To Train Your World Model: Fine-tuning vs RAG for LM-based World Modeling

World models (WMs) simulate the transition dynamics of environments, enabling agents to plan over the consequences of their actions. In text-based environments, fine-tuning a Language Model (LM) to serve as a WM has emerged as a dominant paradigm. However, despite the widespread…

Dhananjay Ashok, Shantanu Agarwal, Vivek Datla, Jonathan May, Alfy Samuel·arXiv — cs.AI

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Key Takeaways

01.World models (WMs) simulate the transition dynamics of environments, enabling agents to plan over the consequences of their actions
02.In text-based environments, fine-tuning a Language Model (LM) to serve as a WM has emerged as a dominant paradigm
03.However, despite the widespread…

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