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Minjae Lee

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#machine learning Preprint Oct 2026

Which Preferences to Train On? End-to-End Multi-Objective Alignment with an Adversarial Preference Distribution

Aligning large language models (LLMs) with human values is important for safe, efficient, and beneficial AI deployment. However, human values are multifaceted: helpfulness, harmlessness and humor trade off against one another, and different users want different trade-offs. Multi-objective alignment (MOA) addresses this...

Minjae Lee, Kyunghyun Cho, Sangdon Park · 0 citations

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