AI RESEARCH
Brain-CLIPLM: Decoding Compressed Semantic Representations in EEG for Language Reconstruction
arXiv CS.CL
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ArXi:2604.16370v1 Announce Type: new Decoding natural language from non-invasive electroencephalography (EEG) remains fundamentally limited by low signal-to-noise ratio and restricted information bandwidth. This raises a fundamental question regarding whether sentence-level linguistic structure can be reliably recovered from such signals.