Does expecting automated grading degrade models’ research taste?
情報源: LessWrong ·
TL;DR: We make 3 open-weights models believe that their answers are being graded by an automated-verifier program, rather than a human. We then measure how well they predict expert reviewers’ judgments of AI-safety research proposals ( the TASTE benchmark ). We induce the belief in two ways: SDF (Synthetic document finetuning) Activation steering. In each of these conditions, the machine-grading belief gives lower expert agreement than the human-grading belief. The models’ explanations also shift toward feasibility and away from conceptual contribution. This raises a concern for automated AI s
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Does expecting automated grading degrade models’ research taste?とは？
Does expecting automated grading degrade models’ research taste? is a 記事 discovery curated from LessWrong. TL;DR: We make 3 open-weights models believe that their answers are being graded by an automated-verifier program, rather than a human. We then measure how well they predict expert
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