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 success of non-parametric approaches suc...
Dhananjay Ashok, Shantanu Agarwal, Vivek Datla et al.
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