AI RESEARCH
EEG-FM-Audit: A Systematic Evaluation and Analysis Pipeline for EEG Foundation Models
arXiv CS.AI
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ArXi:2605.26910v1 Announce Type: cross Large EEG Foundation Models (FMs) have shown great potential for decoding EEG signals across diverse cognitive tasks. However, existing EEG-FM studies exhibit three critical limitations: opaque supervised baseline tuning, unverified contributions of complex learning paradigms, and a lack of transparency in model decision-making. To address these, we propose EEG-FM-Audit, a comprehensive evaluation and analysis pipeline designed to systematize the assessment of EEG-FMs.