10 papers
BrainBench: Benchmarking Large Language Models for Comprehensive EEG Understanding
Yangxuan Zhou, Sha Zhao, Yuning Chen +4
Electroencephalography (EEG) analysis extends beyond assigning predefined labels to recordings; it requires workflows connecting natural-language instructions, signal processing, q…
BrainAgent: A Large Language Model-Driven Multi-Agent Framework for Autonomous Brain Signal Understanding
Yangxuan Zhou, Sha Zhao, Jiquan Wang +2
Brain-Computer Interfaces (BCIs) and brain signal understanding are pivotal for clinical health and next-generation interactions. Despite this significance, its widespread adoption…
EvoBrain: Continual Learning of EEG Foundation Models Across Heterogeneous BCI Tasks
Yangxuan Zhou, Sha Zhao, Jiquan Wang +2
Electroencephalography (EEG) is the cornerstone of non-invasive brain-computer interfaces (BCIs), yet conventional decoding relies on fragmented, task-specific architectures that s…
SleepVLM: A Rule-Grounded Vision-Language Model for Auditable Sleep Staging
Guifeng Deng, Pan Wang, Mengfan Niu +9
Sleep staging is essential for sleep assessment and disorder diagnosis. In recent years, automatic sleep staging systems have achieved accuracy approaching that of human experts, b…
DeeperBrain: A Neuro-Grounded EEG Foundation Model Towards Universal BCI
Jiquan Wang, Sha Zhao, Yangxuan Zhou +3
Electroencephalography (EEG) foundation models hold significant promise for universal Brain-Computer Interfaces (BCIs). However, existing approaches often rely on end-to-end fine-t…
CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
Jiquan Wang, Sha Zhao, Zhiling Luo +5
Electroencephalography (EEG) is a non-invasive technique to measure and record brain electrical activity, widely used in various BCI and healthcare applications. Early EEG decoding…