RAG-based EEG-to-Text Translation Using Deep Learning and LLMs

In three linesRAG pipeline for EEG-to-text decoding combining an EEG encoder aligned with semantic embeddings, vector retrieval, and an LLM. On ZuCo dataset, the method outperforms random baseline with cosine similarity of 0.181±0.022 vs 0.139±0.029 (30.45% improvement), without teacher forcing at inference.

Summary generated by Claude — human-verified