AI RESEARCH
BandVQ: Band-Wise Vector-Quantized EEG Foundation Model
arXiv CS.LG
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ArXi:2605.24921v1 Announce Type: new A central challenge in electroencephalography (EEG) foundation modeling is learning transferable representations across recordings with diverse tasks, montages, references, and spectral characteristics. Existing masked modeling approaches often rely on broadband continuous patches or a single discrete representation, which may underrepresent frequency-specific activity.