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EEG-VID: Task-Guided Latent Predictive Pretraining for EEG Decoding and Assistive Target Selection
We propose EEG-VID, a task-guided latent predictive pretraining framework for EEG decoding under session and subject shifts. EEG-VID predicts future latent EEG states from recent history using an exponential-moving-average target encoder and weak task guidance, followed by supervised fine-tuning. Across VIG-48 and BCI Competition IV-2a/IV-2b, Stage 1 improves mean accuracy in 41 of 42 matched backbone-dataset-protocol comparisons, including all 12 leave-one-subject-out settings, with a maximum gain of 16.22 percentage points. On the 48-region cross-day VIG-48 task, EEG-VID achieves 6.52% Top-1
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T02:00:58.000Z
First collected: 2026-09-21T06:21:59.299Z. This is not the publication date.