Brain2Qwerty v2
End-to-end deep learning pipeline that decodes text in real time from non-invasive magnetoencephalography (MEG) brain recordings, requiring no surgical implant. Trained on approximately 22,000 sentences from nine participants, it achieves 61% word accuracy -- far above the 8% benchmark for other non-invasive methods -- by fine-tuning large language models on raw neural signals.
- Type
- Multimodal
- Weights
- Closed
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