AINeutralarXiv – CS AI · 10h ago6/10
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Personalized Alignment Revisited: The Necessity and Sufficiency of User Diversity
This theoretical computer science paper establishes formal conditions for efficient personalized alignment in large language models, proving that user diversity—specifically whether user-specific parameters span latent reward directions—is both necessary and sufficient for optimal statistical efficiency. The research provides rigorous mathematical foundations for adapting AI systems to heterogeneous user preferences.