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ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification (2022.lrec-1)

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Challenge: Recent advances in natural language processing (NLP) have reshaped the industry . complexity of such models makes them a “black box” and can cause ethical concerns .
Approach: They propose a convolutional TM architecture that breaks down text into a sequence of fragments . they propose to use a tokenization scheme to bind the tokens to the text fragments.
Outcome: The proposed architecture improves on a set of text fragments and eliminates the need for a corpus-specific vocabulary.

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