NeuroMM Grand Challenge

Epilepsy remains a high-impact testbed for trustworthy AI, where Interictal Epileptiform Discharges (IEDs) are critical biomarkers for diagnosis and localization. Existing methods are often EEG-only and do not fully exploit multimodal context, leading to limited robustness under class imbalance, biological variability, and real-world noise.

NeuroMM 2026 addresses this gap by introducing a multimodal challenge framework that integrates physiological signals with synchronized contextual information. The challenge is designed to advance robust multimodal perception, cross-modal reasoning, and clinically actionable inference.

The challenge includes three official tracks: NMM-Basic-IED, NMM-Context-IED, and NMM-Source-IED, covering detection, context-aware robustness, and spatial localization.

• The first-place paper of each track will be recommended to the ACM MM main conference proceedings.
• Other ranked teams are also welcome to prepare papers and submit to the NeuroMM 2026 workshop.
• At least one main-conference full registration is required for each accepted paper.

We will publish detailed tutorials, registration instructions, submission guidance, and the official participation website information in a later update. Please stay tuned.

Code

Baseline code and starter toolkit are currently under final cleanup and documentation. We will release them soon. Please stay tuned.

Advisory Committee

Fei Ma

Guangming Laboratory

Zitong Yu

Great Bay University

Zheng Lian

Tongji University

Laizhong Cui

Shenzhen University

Qi Tian

Guangming Laboratory & Huawei