Preprint
Aug 2026
Learning to Adapt Cross-Domain Preferences via Meta-LoRA for LLM Personalization
PAC-Bayes-regularized Meta-LoRA is proposed, which uses a meta-learned LoRA initialization as both the adaptation start and prior center, while adjusting update strength according to support-set size and predictive uncertainty to limit overfitting under sparse or ambiguous evidence.
Xuefei Wang, Jun Han, Zi-Xuan Wang et al.
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