Large language models (LLMs) have achieved remarkable success across diverse applications, yet their generic training paradigm limits effectiveness in user-specific scenarios. LLM personalization aims to adapt large models to individual users or user groups by incorporating preferences, histories, and contextual signal...
Rui-Jie Wang, Qing-Kai Zeng, Xuefei Wang et al.· Proceedings of the 32nd ACM...· 0 citations
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.· 0 citations
Ide Search is proposed, a framework that systematically integrates a dynamic"Idea Bank" into Tree Search, a framework that systematically integrates a dynamic bank of ideas into Tree Search, and reliably breaks the plateau of a strong pure Tree Search baseline.
Xuefei Wang, Hao Cui, Michael P. Brenner et al.· 0 citations
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