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However, these\narchitectures are rather shallow in comparison to the deep convolutional\nnetworks which have pushed the state-of-the-art in computer vision. We present\na new architecture (VDCNN) for text processing which operates directly at the\ncharacter level and uses only small convolutions and pooling operations. We are\nable to show that the performance of this model increases with depth: using up\nto 29 convolutional layers, we report improvements over the state-of-the-art on\nseveral public text classification tasks. 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