2026
CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure
ICLR 2026poster
Low-rank architectures have become increasingly important for efficient large language model (LLM) pre-training, providing substantial reductions in both parameter complexity and memory/computational demands. Despite these advantages, current low-rank methods face three critical shortcomings: (1) co…