Replacing the feed-forward networks of a tiny BERT with four-qubit quantum circuits yielded 81.19% versus 79.59% on SST-2, but the result rests on a single seed and a CLS-only circuit application.
Improving Language Understanding by Generative Pre-Training,
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QFFN-BERT: An Empirical Study of Depth, Performance, and Data Efficiency in Hybrid Quantum-Classical Transformers
Replacing the feed-forward networks of a tiny BERT with four-qubit quantum circuits yielded 81.19% versus 79.59% on SST-2, but the result rests on a single seed and a CLS-only circuit application.