Brain-CLIPLM
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Brain-CLIPLM: Semantic Compression for EEG-to-Text Decoding
Announce Type: replace Abstract: Decoding natural language from non-invasive electroencephalography (EEG) remains constrained by low signal-to-noise ratio and limited information bandwidth. This raises a central question: can sentence-level language be reliably recovered from such signals? Under realistic information constraints, this direct-recovery assumption may be too strong.