deberta-disentangled-attention-three-matrices

Summary

DeBERTa's architecture deliberately keeps a word's meaning separate from its position in the sentence, then runs three distinct attention passes so the model can reason about word-to-word, position-to-word, and position-to-position relationships independently. For the system, this matters because it means DeBERTa's performance advantage comes from a structural separation of concerns rather than raw scale, so any comparison or downstream use should expect it to handle position-sensitive language tasks more cleanly than a standard BERT-style transformer.