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QNN gate selection and arrangement, not just qubit count, critically dictate financial forecasting performance, with the best configuration outperforming classical BiLSTM and exhibiting significant noise sensitivity on current quantum hardware.
Hybrid quantum-classical models can significantly boost sentiment analysis performance, achieving a 15-point accuracy leap in spam classification tasks.