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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.
Ditch the resampling: ReIMTS forecasts irregular time series 27% better by recursively splitting data and preserving original timestamps, unlocking crucial sampling pattern information.
