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Optimizing the Score, Losing Sight of the Task: Reward Hacking Across Weights, Selection, and Prompts
A higher evaluation score does not always mean a better language model system. When optimization exploits an evaluator's mistakes, measured progress can conceal unchanged or deteriorating task performance. This failure can arise through parameter updates, selection among generated outputs, or revisi
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