Papers with high-quality text classifiers

1 papers
META: Metadata-Empowered Weak Supervision for Text Classification (2020.emnlp-main)

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Challenge: Existing methods for weakly supervised text classification use text data alone to generate pseudo-labels . strong label indicators exist in metadata and it has been long overlooked due to challenges .
Approach: They propose a framework that leverages metadata as an additional source of weak supervision by combining text data and metadata into a text-rich network.
Outcome: The proposed framework exploits metadata as an additional source of weak supervision.

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