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cs.LG2026
Benchmarking EEG Foundation Models at Scale: Lessons from 20,000 Evaluations
Zhige Chen, Shu Peng, Chengxuan Qin +4
Electroencephalography (EEG) foundation models (FMs) promise transferable neural representations, yet their advantages over strong supervised baselines and their prospects for furt…
cs.LG2026
EEG Benchmarking Needs a Task Specification Layer: NeuroDoc for Rulebook-Guided, Executable Benchmark Construction
Chengxuan Qin, Zhige Chen, Shu Peng +9
Electroencephalography (EEG) foundation models increasingly rely on multi-dataset training and evaluation, yet public EEG datasets still lack a shared task specification layer that…