RulePrompt introduces a new method for weakly supervised text classification by incorporating logical rules to improve category understanding. The approach outperforms existing methods on various datasets, showcasing its effectiveness and interpretability.
The paper addresses the challenges of weakly supervised text classification by introducing logical rules to enhance category representation. By iteratively updating pseudo labels and logical rules, RulePrompt achieves significant improvements in classification accuracy compared to state-of-the-art methods.
The proposed approach combines the strengths of prompting PLMs with self-iterative logical rules to create a robust framework for text classification. Extensive experiments demonstrate the superiority of RulePrompt in handling challenging classification tasks across different domains.
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arxiv.org
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by Miaomiao Li,... : arxiv.org 03-06-2024
https://arxiv.org/pdf/2403.02932.pdfDaha Derin Sorular