Overcoming the BCI Calibration Bottleneck: A Clinically-Grounded Architecture using Riemannian Alignment and Stochastic Weight Averaging
arXiv 2607.16225•8185b003e1ef301f577b49f398715a88b72fcf2b2d5eb8cfce270ecdfa22613d
6GAgent-CompilerBCIECG-LLMEEGISACLLM-compilationRISRiemannian alignmentchannel-estimation','attention-scaling','CHEA','PUSCH','sensor-fclinical-AIhybrid-beamforminginfrastructure-automationmassive-MIMOmedical-AImmWavemodel-compressionmultimodal-LLMpolicy-graphprivacyquantizationseizure-detectionspiking-neural-networksstochastic weight averagingzero-calibration
Paper metadata
- arXiv ID
- 2607.16225
- Version
- Not specified by this published record
- Category
- Electrical Engineering and Systems Science — Signal Processing (eess.SP)
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Evidence and limitations
- Source ID
- arxiv_eess_sp
- Record identifier
- 8185b003e1ef301f577b49f398715a88b72fcf2b2d5eb8cfce270ecdfa22613d
- Enrichment time
- 2026-07-21T08:51:39Z
- AI-assisted enrichment
- Yes
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