Ruijia Zhang

Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR

Ruijia Zhang, Jiacheng Zhu, Hanqing Zhu, Laixi Shi

Low-rank adaptation (LoRA) and its variants enable parameter-efficient fine-tuning of large language models under the supervised fine-tuning (SFT) paradigm. However, their efficacy and behavior under Reinforcement learning with verifiable rewards (RLVR) are less well understood.…Read more