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

This story is from 2026-10-06. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2610.02542v1 Announce Type: new Abstract: 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. How…

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  1. 2026-10-06 04:00 · arXiv cs.AI
    How To Train Your World Model: Fine-tuning vs RAG for LM-based World Modeling

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