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By fusing sparse coding with visual Transformers, LISTA-Transformer achieves state-of-the-art fault diagnosis accuracy, surpassing traditional methods by 3.3% on the CWRU dataset.
HiLoRA achieves superior personalization in federated learning by adaptively clustering clients based on LoRA subspace similarity, enabling targeted knowledge sharing and outperforming standard LoRA-based methods.
