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  • Zhiying Jiang, Matthew Y. R. Yang, Mikha...
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    Dec 19th, 2022
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    preprint
    Zhiying Jiang, Matthew Y. R. Yang, Mikha...
    Dec 19th, 2022

    Deep neural networks (DNNs) are often used for text classification tasks as they usually achieve high levels of accuracy. However, DNNs can be computationally intensive with billions of parameters and large amounts of labeled data, which can make them expensive to use, to optimize and to transfer to out-of-distribution (OOD) cases in practice. In this paper, we propose a non-parametric alternative to DNNs that's easy, light-weight and universal in text classification: a combination of a...

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