Papers with DABERTa

1 papers
Empowering the Fact-checkers! Automatic Identification of Claim Spans on Twitter (2022.emnlp-main)

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Challenge: Current vogue is to employ manual fact-checkers to efficiently classify and verify such data to combat this avalanche of misinformation and fake news.
Approach: They propose a large-scale Twitter corpus with token-level claim spans on more than 7.5k tweets and a model that automatically detects and extracts the snippets of misinformation.
Outcome: The proposed model outperforms baseline systems on several evaluation metrics, improving by 1.5 points.

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