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Fine-tuning LLMs in federated settings just got easier: SplitFT lets clients adapt their cut layers and LoRA ranks, boosting performance and slashing communication costs.
By learning radiation transfer across multiple mesh resolutions, nested neural operators make high-fidelity fire simulations practical, opening the door to more spectrally-resolved radiation models.
