3 papers
cs.LG2026
The Identity Trap in EEG Foundation Models: A Diagnostic Audit
Jun-You Lin, Ying Choon Wu, Tzyy-Ping Jung
Objective. EEG foundation models (FMs) report strong accuracy on clinical resting-state EEG. However, high accuracy under subject-disjoint cross-validation remains ambiguous: it ca…
cs.LG2025
IMU-Enhanced EEG Motion Artifact Removal with Fine-Tuned Large Brain Models
Yuhong Zhang, Xusheng Zhu, Yuchen Xu +4
Electroencephalography (EEG) is a non-invasive method for measuring brain activity with high temporal resolution; however, EEG signals often exhibit low signal-to-noise ratios beca…
cs.CL2025
Graph Representations for Reading Comprehension Analysis using Large Language Model and Eye-Tracking Biomarker
Yuhong Zhang, Jialu Li, Shilai Yang +3
Reading comprehension is a fundamental skill in human cognitive development. With the advancement of Large Language Models (LLMs), there is a growing need to compare how humans and…