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Explicitly conditioning sleep representations on global time-of-sleep dramatically boosts performance on challenging pediatric sleep tasks, even across different datasets and models.
Random-pair cross-attention unlocks robust multimodal sleep representations, outperforming baselines on respiratory tasks and generalizing effectively to new datasets.