Benchmarking EEG Foundation Models at Scale: Lessons from 20,000 Evaluations
cs.LG, eess.SP
Submitted: 2026-09-26
Updated: 2026-09-26
Terminology
Sources
- NeuralBench: A Unifying Framework to Benchmark NeuroAI Models
- NeuroRVQ: Multi-Scale Biosignal Tokenization for Generative Foundation Models
- HEAR: An EEG Foundation Model with Heterogeneous Electrode Adaptive Representation
- NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces
- OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models
- FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface
- Brain4FMs: A Benchmark of Foundation Models for Electrical Brain Signal
- LEAD: An EEG Foundation Model for Alzheimer's Disease Detection
- AdaBrain-Bench: Benchmarking Brain Foundation Models for Brain-Computer Interface Applications
- EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation and Diagnostic Analyses of EEG Foundation Models
- Multi-dataset Joint Pre-training of Emotional EEG Enables Generalizable Affective Computing
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks