Papers by Keqian Li

1 papers
TNT: Text Normalization based Pre-training of Transformers for Content Moderation (2020.emnlp-main)

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Challenge: Language model pre-training (self-supervised or unsupervised learning) has been widely used in a multitude of language processing tasks such as named entity recognition, sentiment analysis, question answering and content moderation.
Approach: They propose a new language pre-training model TNT for content moderation that uses a combination of masking strategy and text normalization to learn from text.
Outcome: The proposed model outperforms baselines on hate speech classification task and is a potential approach to misspelling correction.

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