Transfer learning with BERT models classifies quantum software engineering challenges from Stack Overflow posts into six categories at 95% average accuracy, outperforming traditional ML baselines by 6% and adding SHAP interpretability.
Architecture decisions in quantum soft- ware systems: An empirical study on stack exchange and github
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An Improved Quantum Software Challenges Classification Approach using Transfer Learning and Explainable AI
Transfer learning with BERT models classifies quantum software engineering challenges from Stack Overflow posts into six categories at 95% average accuracy, outperforming traditional ML baselines by 6% and adding SHAP interpretability.