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papersTODAY 04:00 UTC

S-CEReBrO Architecture Targets Memory Limits in Continuous EEG Monitoring

A new arXiv paper introduces S-CEReBrO, an approach aimed at overcoming the memory constraints that arise when applying Transformer-based foundation models to long-running EEG recordings. Global attention scales poorly with signal length, which limits how far such models can be used for continuous brain-monitoring data. The work proposes a redesign intended to make long-sequence EEG analysis more tractable while retaining the generalization benefits of large pretrained models.

arXiv S-CEReBrO Transformer-based foundation models continuous EEG monitoring global attention long-sequence EEG analysis

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arXiv cs.LGS-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring ↗TODAY 04:00 UTC