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It is observed that the natural language of problem statements affects LLM-based code generation performance and translation improved Accuracy, but its effectiveness was not consistent across datasets and model types.
RepTran achieves a remarkable 74.7% repair rate for Transformer models, significantly outperforming existing repair methods.
