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Stephen Casper

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#machine learning Preprint Sep 2026

From Constitutions to Control: Interpretable Rewards for Aligning Language Models

Current approaches to aligning language models often make it hard to know what behavior is being rewarded or to change that reward in a targeted way. In particular, standard preference-based methods collapse multiple considerations into aggregate human judgments, obscuring what drives the resulting reward, while princi...

Johann D. Gaebler, C. Isley, Max Lamparth et al. · 0 citations

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