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The paper proposes a novel deep learning-based method for improving the accuracy and efficiency of natural language processing tasks, using a combination of self-attention and convolution mechanisms. The method demonstrates state-of-the-art performance on several benchmark datasets for tasks such as sentiment analysis and question answering.