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Rui-Xin Guo

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#artificial intelligence Preprint Sep 2026

Gradient-Aligned Pair Selection for Personalized Preference Optimization

Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Direct Preference Optimization (DPO) provides a stable framework for preference learning, its effectiveness in personalized settings critically depends on how preference p...

Ruo-Ming Jin, Xin-Yu Li, Hao Zhou et al. · 0 citations
#artificial intelligence Preprint Sep 2026

PLUME: Parameter-Efficient Personalization of Large Language Models via Low-Rank User Modulation in Shared Subspaces

Personalizing large language models (LLMs) is essential for delivering AI assistance that aligns with individual users'styles, intents, and preferences. While per-user fine-tuning can substantially enhance personalization quality, it introduces significant parameter and storage overhead, limiting scalability to large u...

Xin-Yu Li, Hao Zhou, Jian-Feng Zhu et al. · 0 citations

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