Preference fine-tuning outperforms prompting for personalisation but amplifies sycophancy and relationship-seeking, while simulated users recover aggregate rankings yet show far lower self-consistency and different topic and position biases than real humans.
The autograder receives the user’s persona profile to assess whether the model’s re- sponse draws on stereotypical assumptions
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PRISM-X: Experiments on Personalised Fine-Tuning with Human and Simulated Users
Preference fine-tuning outperforms prompting for personalisation but amplifies sycophancy and relationship-seeking, while simulated users recover aggregate rankings yet show far lower self-consistency and different topic and position biases than real humans.