papersSEP 10 04:00 UTC
Verified Code World Models Proposed to Cheaply Scale LLM Domain Generalization
A new paper examines how large language models can generalize in domains that lack abundant real, labeled examples. By expressing a domain's dynamics as code, the authors show a single template can instantiate many simulated world models whose executions yield verified training data. The goal is to manufacture generalization examples cheaply where real-world annotation is scarce.