Papers by Yuanjin Zheng

1 papers
MTA:A Merge-then-Adapt Framework for Personalized Large Language Models (2026.acl-long)

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Challenge: Personalized Large Language Models (PLLMs) aim to align outputs with individual user preferences . current methods of fine-tuning a separate module for each user are unscalable .
Approach: They propose a Merge-then-Adapt framework for Personalized Large Language Models . they construct a shared Meta-LoRA bank and propose an Adaptive LoRA Fusion stage .
Outcome: The proposed framework outperforms existing SOTA methods on the LaMP benchmark.

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