Qiran Zhang

Qiran Zhang

Undergraduate student in Artificial Intelligence at Shanghai Jiao Tong University.

CerebraGloss: Instruction-Tuning a Large Vision-Language Model for Fine-Grained Clinical EEG Interpretation

Published in ICLR 2026, 2026

Links: OpenReview ยท Code

CerebraGloss studies how large vision-language models can support fine-grained clinical EEG interpretation. The work introduces an automated EEG-text data generation pipeline, an instruction-tuned LVLM, and CerebraGloss-Bench for open-ended EEG interpretation.

Highlights

  • Builds a programmatic EEG-text instruction data engine with waveform, artifact, and background characterization.
  • Trains a model for detailed waveform description, multi-choice reasoning, and multi-turn EEG dialogue.
  • Evaluates the model on CerebraGloss-Bench and downstream clinical tasks such as seizure detection and sleep staging.

Recommended citation: Wei Gu, Tianming Luo, Qiran Zhang, Mohan Ye, Xiao Shen, Wenxin Chen, Yunhuan Li, Yichen Zhang, Jing Hong, Bao-liang Lu, and Wei-Long Zheng. (2026). "CerebraGloss: Instruction-Tuning a Large Vision-Language Model for Fine-Grained Clinical EEG Interpretation." ICLR.
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