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Brain-computer interfaces decode neural activity, yet class-label supervision (CLS) leaves relationships among classes implicit. We propose Language as Supervision (LaS), which aligns neural features with natural-language class descriptions through learned projections and predicts classes using candidate text prototype...
This work presents a calibration-focused dataset containing 163 trials from 12 participants, with separate 18-point fitting and 32-point test grids, and uses it to evaluate global, local, and composite correction functions under a common spatial-extrapolation protocol and introduces a lightweight neural refiner that co...
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