Event Type Classification on TUEV
70.8Balanced AccuracyKAST-BAR-Large
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| KAST-BAR-LargeModel Parameter=2.2B, General Model=true, Multi-Task=true2026.05 | 70.8 | 69.6 | 85.5 | |
| CSBrainModel Parameter=4.9M, General Model=true, Multi-Task=false2026.05 | 69 | 68.3 | 83.3 | |
| CBraModModel Parameter=4.0M, General Model=true, Multi-Task=false2026.05 | 66.7 | 67.7 | 83.4 | |
| KAST-BAR-BaseModel Parameter=0.8B, General Model=true, Multi-Task=true2026.05 | 66.1 | 64.7 | 82.8 | |
| DARE-EEGArchitecture=Base2026.05 | 65.61 | 0.5827 | 78.84 | |
| THD-BAR-HugeModel Parameter=1.6B, General Model=true, Multi-Task=true2026.05 | 65.3 | 64.4 | 82.1 | |
| MTEEG-DC# Trainable Params=1.1M, Training Paradigm=Multi-task2026.04 | 65.21 | 0.6398 | 82.09 | |
| DARE-EEGArchitecture=Deep2026.05 | 64.89 | 0.5883 | 79.2 | |
| MTEEG-SP# Trainable Params=1.8M, Training Paradigm=Multi-task2026.04 | 64.38 | 0.6281 | 81.84 | |
| LaBraM# Trainable Params=5.8M, Training Paradigm=Single-task, Finetuning Strategy=Full2026.04 | 64.36 | 0.6254 | 81.72 | |
| LaBraM# Trainable Params=0.3M, Training Paradigm=Single-task, Finetuning Strategy=LoRA2026.04 | 64.31 | 0.6111 | 81.03 | |
| LaBraM-BaseModel Parameter=5.8M, General Model=true, Multi-Task=false2026.05 | 64.1 | 66.4 | 83.1 | |
| EEGPTsize=large2026.05 | 62.32 | 0.6351 | 81.87 | |
| EEGPTModel Parameter=25M, General Model=true, Multi-Task=true2026.05 | 62.3 | 63.5 | 81.9 | |
| HPS# Trainable Params=6.0M, Training Paradigm=Multi-task2026.04 | 60.93 | 0.6097 | 81.09 | |
| TFM-Tokenizer†Model Size=1.9M, Training Setting=Multiple Dataset Pretraining, Pretraining_Scope=4 EEG datasets2025.02 | 59.74 | 0.6189 | 80.1 | |
| CBraMod†Model Size=4M, Training Setting=Multiple Dataset Pretraining, Pretraining_Scope=4 EEG datasets2025.02 | 56.96 | 0.5588 | 77.02 | |
| EEGPTModel Size=4.7M, Training Setting=Multiple Dataset Pretraining2025.02 | 56.7 | 0.5085 | 75.35 | |
| EEGPTsize=tiny2026.05 | 56.7 | 0.5085 | 75.35 | |
| MTEEG-RT# Trainable Params=1.8M, Training Paradigm=Multi-task2026.04 | 55.74 | 0.5852 | 79.81 | |
| LaBraM-Base†Model Size=5.8M, Training Setting=Multiple Dataset Pretraining, Pretraining_Scope=4 EEG datasets2025.02 | 55.5 | 0.5175 | 74.5 | |
| BIOT# Trainable Params=3.2M, Training Paradigm=Single-task2026.04 | 52.81 | 0.5273 | 74.92 | |
| BIOTModel Size=3.2M, Training Setting=Multiple Dataset Pretraining2025.02 | 52.81 | 0.5273 | 74.92 | |
| BIOTvariant=Other2026.05 | 52.81 | 0.5273 | 74.92 | |
| BIOTModel Parameter=3.2M, General Model=true, Multi-Task=false2026.05 | 52.8 | 52.7 | 74.9 | |
| BIOTvariant=PREST2026.05 | 52.07 | 0.4932 | 73.81 | |
| TFM-TokenizerModel Size=1.9M, Training Setting=Single Dataset Setting2025.02 | 49.43 | 0.5337 | 75.7 | |
| Vanilla BIOTModel Size=3.2M, Training Setting=Single Dataset Setting2025.02 | 46.82 | 0.4482 | 70.85 | |
| LaBraM-Base*Model Size=5.8M, Training Setting=Single Dataset Setting, Reproduced=true2025.02 | 46.82 | 0.5067 | 74.66 | |
| NeuroLM-XLModel Parameter=1.7B, General Model=true, Multi-Task=true2026.05 | 46.8 | 45.7 | 73.6 | |
| BIOT*Model Size=3.2M, Training Setting=Single Dataset Setting, Reproduced=true2025.02 | 46.79 | 0.489 | 73.52 | |
| NeuroLM-BModel Size=254M, Training Setting=Multiple Dataset Pretraining2025.02 | 45.6 | 0.4285 | 71.53 | |
| ContraWR# Trainable Params=1.6M, Training Paradigm=Single-task2026.04 | 43.84 | 0.3912 | 68.93 | |
| ContraWRModel Size=1.6M, Training Setting=Single Dataset Setting2025.02 | 43.84 | 0.3912 | 68.93 | |
| ContraWR2026.05 | 43.84 | 0.3912 | 68.93 | |
| SPaRCNetModel Parameter=0.79M, General Model=false, Multi-Task=false2026.05 | 43.2 | 43.8 | 68.1 | |
| SPaRCNet# Trainable Params=0.79M, Training Paradigm=Single-task2026.04 | 41.61 | 0.4233 | 70.24 | |
| SPaRCNetModel Size=0.79M, Training Setting=Single Dataset Setting2025.02 | 41.61 | 0.4233 | 70.24 | |
| SPaRCNet2026.05 | 41.61 | 0.4233 | 70.24 | |
| CNN-Transformer# Trainable Params=3.2M, Training Paradigm=Single-task2026.04 | 40.87 | 0.3815 | 68.54 | |
| CNN-TransformerModel Size=3.2M, Training Setting=Single Dataset Setting2025.02 | 40.87 | 0.3815 | 68.54 | |
| CNN-Trans2026.05 | 40.87 | 0.3815 | 68.54 | |
| ST-Transformer# Trainable Params=3.5M, Training Paradigm=Single-task2026.04 | 39.84 | 0.3765 | 68.23 | |
| ST-TransformerModel Size=3.5M, Training Setting=Single Dataset Setting2025.02 | 39.84 | 0.3765 | 68.23 | |
| ST-Trans2026.05 | 39.84 | 0.3765 | 68.23 | |
| EEGNetGeneral Model=false, Multi-Task=false2026.05 | 39.8 | 34.9 | 63.8 | |
| FFCL# Trainable Params=2.4M, Training Paradigm=Single-task2026.04 | 39.79 | 0.3732 | 67.83 | |
| FFCLModel Size=2.4M, Training Setting=Single Dataset Setting2025.02 | 39.79 | 0.3732 | 67.83 | |
| FFCL2026.05 | 39.79 | 0.3732 | 67.83 | |
| ST-TransformerModel Parameter=3.5M, General Model=false, Multi-Task=false2026.05 | 39.6 | 38.3 | 69.1 |