A research paper finds that general-purpose large language models already function as Jev-style decision models, returning categorical probability distributions over predefined options without generating free-form text, and examines when and how to fine-tune them for that use. The work investigates the extent to which LLMs possess this capability out of the box, which matters because such outputs let software systems act on model decisions directly.
Jev-style decision models return categorical probability distributions over predefined options without generating free-form text, enabling software systems to act on their outputs directly. In this work, we investigate the extent to which general-purpose LLMs already possess this capability out of t
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