Yan Xiaodong

HiMoLE: Towards OOD-Robust LoRA via Hierarchical Mixture of Experts

Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, have enabled the efficient adaptation of large language models (LLMs) by updating only a small subset of parameters. However, their robustness under out-of-distribution (OOD) conditions remains insufficiently studied. In this paper, we id…