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Junzhu Liang

1 accepted papers

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…

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