Efficient Personalization of Generative Models via Optimal Experimental Design

arXiv:2512.19057v2 Announce Type: replace-cross Abstract: Preference learning from human feedback has the ability to align generative models with the needs of end-users. Human feedback is costly and time-consuming to obtain, which creates demand for data-efficient query select...

🔗 Read more: https://arxiv.org/abs/2512.19057

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